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Showing posts with label Vulnerabilities and Exploits. Show all posts
Vulnerabilities and Exploits
PostgreSQL RCE Splunk Unauthorised Access Vulnerabilities and Exploits

Critical Splunk Enterprise Flaw Lets Attackers Run Code Without Authentication

 

Splunk has issued urgent security updates to address a catastrophic vulnerability in Splunk Enterprise that enables unauthenticated remote code execution (RCE). Tracked as CVE-2026-20253, the flaw carries a maximum CVSS score of 9.8, marking it as one of the most severe security issues seen in enterprise data platforms this year. Attackers can exploit this vulnerability to perform arbitrary file operations and execute malicious code without providing any credentials, potentially leading to complete infrastructure compromise. 

The vulnerability stems from the PostgreSQL Sidecar Service introduced in Splunk version 10, which lacks proper authentication controls at its endpoint. Specifically, the service listens locally on port 5435 and allows any network-reachable user to invoke file operations without credentials. According to Splunk's official alert, "an unauthenticated user could create or truncate arbitrary files through a PostgreSQL sidecar service endpoint" in versions below 10.2.4 and 10.0.7. This missing authentication layer transforms what appeared to be an arbitrary file-creation issue into a full-blown unauthenticated RCE vulnerability. 

Affected versions include all Splunk Enterprise releases below 10.2.4 and 10.0.7, impacting multiple release branches across the 10.x series. The flaw specifically targets the PostgreSQL Sidecar Service API, which was introduced as part of Splunk version 10's architecture. Cybersecurity experts warn that due to the potential for full infrastructure compromise in both enterprise and cloud environments, immediate patching is absolutely required. Organizations running unpatched Splunk instances face extreme risk since the vulnerability requires no authentication whatsoever. 

Splunk has released security updates that properly address this critical flaw by implementing authentication controls at the PostgreSQL Sidecar Service endpoint. Security administrators should prioritize upgrading to version 10.2.4 or 10.0.7 (or newer) immediately to close this attack vector. The cybersecurity community has noted the ironic danger here: Splunk is supposed to be your security monitoring tool, so if this unpatched vulnerability sits on your network, attackers can bypass your very security infrastructure. No active detections in the wild have been confirmed yet, but the severity makes this a likely target for rapid exploitation. 

This vulnerability represents a critical security gap that demands immediate attention from all Splunk Enterprise users worldwide. With a CVSS score of 9.8, CVE-2026-20253 elevates what was initially reported as an arbitrary file-creation flaw into a dangerous unauthenticated remote code execution threat. Organizations must treat this as a top-priority security incident and apply Splunk's patches without delay to prevent potential data breaches, system compromise, or complete infrastructure takeover by malicious actors.
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Vulnerabilities and Exploits
AI Agent Security AI Phishing Attacks OpenClaw security vulnerability prompt injection attack Vulnerabilities and Exploits

OpenClaw Security Flaws Expose AI Agents to Hidden Commands and Data Theft Risks

 

Two independent cybersecurity studies published this week have uncovered serious security weaknesses in OpenClaw, a widely used self-hosted AI agent platform. The findings demonstrate how attackers can manipulate AI agents into executing malicious code or leaking sensitive information through seemingly harmless inputs.

Researchers from Imperva and Varonis approached the issue from different angles but reached a similar conclusion: AI agents that trust incoming data and possess broad system access can become powerful attack vectors when exploited.

Hidden Instructions Embedded in Everyday Content

Imperva researchers discovered that OpenClaw could be tricked into processing concealed instructions embedded within shared contacts, vCards, and location pins. These malicious commands were executed by the AI agent without any visible indication to the user.

The issue stemmed from how OpenClaw handled certain message objects before passing them to the large language model (LLM). While content fetched from the web was clearly marked as untrusted, information contained within contacts, vCards, and location labels was inserted directly into prompts without any trust boundary.

According to Imperva researcher Yohann Sillam, this allowed attackers to hide instructions inside fields such as contact names. Since angle brackets are permitted in contact names, the model could not reliably distinguish legitimate information from injected commands.

Only selected fields were transmitted to the model, making them attractive targets. In one example, a shared contact was serialized as <contact: name, number>, allowing attackers to insert malicious instructions within the name field itself. Because messaging apps truncate long contact names, victims often never saw the hidden payload.

The same attack method was also successful through WhatsApp-supported vCards and shared location labels.

During testing against Gemini 3.1 Pro's preview build, hidden instructions successfully convinced the AI agent to download and execute a script hosted on servers controlled by the researchers. Similar attempts using images with embedded instructions failed, likely because AI models have become more resistant to that well-known attack technique.

Imperva warned that OpenClaw's default memory functionality could amplify the threat. A single malicious piece of widely shared content could potentially affect multiple agents if adequate sandboxing protections were absent.

Following responsible disclosure, OpenClaw addressed the issue in version 2026.4.23. The update separates contact names, vCard information, and location labels from the main prompt and places them in an isolated untrusted metadata channel.

Researchers also noted that similar design patterns exist in several other personal AI assistant platforms, suggesting the issue extends beyond OpenClaw alone.

Social Engineering Defeats Technical Safeguards

While Imperva focused on prompt injection, Varonis Threat Labs explored how AI agents respond to social engineering attacks.

Led by researcher Itay Yashar, the Varonis team created an OpenClaw-based agent called Pinchy and connected it to a Gmail inbox filled with realistic business communications and synthetic sensitive information. The researchers then tested the agent using four different phishing scenarios involving Google Gemini 3.1 Pro and OpenAI Codex GPT-5.4.

Varonis distinguishes traditional prompt injection from what it calls "agent phishing." Unlike hidden instructions embedded in content, agent phishing relies on convincing requests delivered through normal communication channels, exploiting the agent's willingness to act before verifying legitimacy.

The tests revealed significant weaknesses.

In one scenario, an email impersonating a team leader named Dan requested urgent staging access during a simulated production emergency. The message originated from an external Gmail account, yet the agent located and forwarded mock AWS IAM access keys, database connection credentials, and SSH details in plain text.

A second phishing attempt used a more routine business request, asking for a weekly customer export supposedly needed for a QBR presentation. The agent responded by sending a synthetic database containing information on 247 enterprise customers, including contact details and contract values.

Notably, these failures occurred despite the agent being configured with instructions to verify sender identities before responding. Researchers observed that urgency successfully bypassed safeguards in one case, while routine business language defeated them in another.

The agent demonstrated stronger performance against technically oriented threats. It interacted with a phishing page designed to steal gift-card credentials but ultimately withheld sensitive information and flagged suspicious behavior. A stricter configuration blocked the page entirely.

Similarly, when presented with a malicious OAuth consent screen disguised as a timesheet application, the agent examined the redirect destination, recognized warning signs, and refused access.

Researchers concluded that AI agents may outperform many users when identifying suspicious URLs and fraudulent login portals. However, they remain vulnerable to social manipulation that exploits helpfulness and trust.

Varonis also observed that OpenAI Codex GPT-5.4 behaved more cautiously than Gemini 3.1 Pro when interacting with external websites or transmitting data. Nevertheless, both models ultimately fell victim to the social-engineering scenarios.

One Core Problem Behind Multiple Attacks

Varonis linked both attack methods to what researcher Simon Willison describes as the "lethal trifecta": an AI system capable of accessing private data, consuming untrusted content, and transmitting information externally.

OpenClaw satisfies all three conditions, making both hidden prompt injections and phishing-based attacks highly effective.

Additional concerns emerged from a separate InfoSec Write-ups analysis. Researchers converted historical OpenClaw security advisories into static-analysis rules and uncovered five additional vulnerabilities affecting integrations with Slack, Discord, Matrix, Zalo, and Microsoft Teams.

Each flaw originated from the same design issue. Channel allowlists were validated using mutable display names rather than permanent identifiers. Attackers could therefore impersonate trusted users simply by changing their display names to match approved accounts.

OpenClaw has since patched these vulnerabilities.

The platform's extensive permissions—including access to files, shell environments, and more than twenty messaging services—have previously prompted warnings regarding prompt injection and data exfiltration risks.

The strongest criticism came from the Dutch data protection authority, the Autoriteit Persoonsgegevens, which advised users and organizations against deploying OpenClaw on systems containing sensitive information due to concerns over data breaches and account compromise.

Recommended Defenses

Organizations using OpenClaw are advised to upgrade immediately to version 2026.4.23 or newer to mitigate the message-object vulnerability identified by Imperva.

However, researchers stress that software updates alone cannot solve the broader trust problem inherent in autonomous AI systems.

Varonis recommends four key safeguards:

  • Treat agent instruction files as strict, version-controlled policies rather than informal guidance.

  • Require approval before agents send messages to unfamiliar recipients, reducing the risk of automated phishing or data leakage.

  • Restrict access to connected systems based on the trustworthiness of the triggering source.

  • Require human review for high-risk actions such as credential sharing, financial transactions, or sensitive data transfers.

Both research teams ultimately advocate the same mindset. Varonis recommends treating AI agents as inexperienced employees with extensive system access but limited judgment, while Imperva describes them as authenticated executors that inherently trust incoming information.

Although vendors continue to introduce patches and protective controls, the fundamental challenge remains unresolved. AI agents derive their usefulness from acting on instructions, processing inputs, and helping users accomplish tasks. Those same characteristics also create opportunities for attackers, and the industry has yet to develop a universal solution.

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Vulnerabilities and Exploits
Authentication Bypass CVE-2026-35616 EKZ Infostealer FortiClient EMS Fortinet vulnerability Vulnerabilities and Exploits

Hackers Exploit FortiClient EMS Flaw to Deploy EKZ Credential-Stealing Malware

 

Cybersecurity researchers have uncovered active attacks exploiting a critical vulnerability in FortiClient Enterprise Management Server (EMS) to distribute a previously undocumented credential-stealing malware known as EKZ Infostealer.

The attacks leverage CVE-2026-35616, an authentication bypass flaw in FortiClient EMS that enables unauthenticated remote attackers to execute arbitrary commands or code through specially crafted requests. The vulnerability stems from improper access control mechanisms and has been actively exploited in the wild.

Threat actors reportedly disguised the malware as a legitimate Fortinet endpoint update and delivered it through VPN scripting workflows managed by FortiClient. Fortinet acknowledged the exploitation of the flaw in early April and subsequently issued emergency hotfixes for versions 7.4.5 and 7.4.6 of the software.

Following reports of malicious activity, the U.S. Cybersecurity and Infrastructure Security Agency (CISA) instructed federal agencies to secure vulnerable systems within days. Around the same period, The Shadowserver Foundation identified approximately 2,000 internet-exposed EMS instances.

Researchers at Arctic Wolf recently observed threat actors using the vulnerability to deploy the EKZ Infostealer. According to the company, attackers begin by abusing endpoint APIs to carry out administrative actions without requiring authentication.

After gaining access, the attackers alter EMS configurations and VPN policies to enable the execution of malicious scripts. Once an endpoint establishes an IPsec connection with a FortiGate firewall, the legitimate FortiClient process, fortitray.exe, launches malicious batch scripts through Command Prompt.

These scripts then execute a Base64-encoded PowerShell payload that downloads malware disguised as a Fortinet software update. The payload subsequently collects data from the victim's device and sends it to an attacker-controlled virtual private server (VPS) over HTTP.

“Rather than relying on a generic malware lure, the payload was presented as a Fortinet endpoint update and executed through FortiClient-managed VPN scripting workflows,” reads the report from Arctic Wolf.

“On affected endpoints, FortiClient components launched command scripts that invoked PowerShell, downloaded a credential stealer, executed it silently, and exfiltrated harvested browser data before removing local artifacts.”

The malware, tracked as EKZ Infostealer, is designed to harvest sensitive information from both Chromium-based and Firefox browsers. It extracts stored browser data into text files and is capable of bypassing encrypted password protections.

Among the targeted data are login credentials, credit card information, addresses, phone numbers, and browser cookies. By stealing cookies, attackers may gain access to accounts protected by multi-factor authentication without needing the user's credentials.

Arctic Wolf noted that one potential indicator of compromise is the appearance of the log entry “Certificate not found in request header.” During testing, this message was often followed within seconds by another log entry indicating that a certificate associated with "fortinet-ca2" had been successfully updated.

Security teams are advised to monitor for unusual certificate authentication events and unauthorized modifications to Remote Access Profile settings. Additionally, suspicious administrative actions, newly created accounts, logins originating from unfamiliar locations such as Tor networks or VPS-hosted IP addresses, and unexpected configuration changes should be treated as potential warning signs of compromise.

Arctic Wolf has also released detailed detection and mitigation guidance to help organizations identify and defend against these attacks.

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Vulnerabilities and Exploits
AI Security Bug Bounty Bug Hunting Security Patch Vulnerabilities and Exploits

AI Era Ignites Bug-Hunting Arms Race as Exploits Accelerate Faster Than Patches

 

The AI era has triggered a new cybersecurity arms race in which attackers and defenders are both using machine learning to find and exploit software vulnerabilities faster than ever. According to security experts, attackers are ramping up AI-powered exploit development, while security teams are deploying AI-driven detection and patching workflows to respond in real time. 

This acceleration is reshaping the economics of software security: the speed of vulnerability discovery no longer matches the slower pace of traditional analysis, triage, and patching, creating a dangerous imbalance between how quickly bugs are found and how quickly they can be fixed. The main issue is the flood of AI-generated bug reports overwhelming existing programs. Curl ended its bug bounty program after being inundated with low-quality submissions generated by AI tools. Linux’s security mailing list has become “almost entirely unmanageable” due to high volumes and duplicate AI bug reports from automated scanners.

Google recently overhauled its Vulnerability Reward Programs for Chrome and Android, lowering payouts for some bug classes while increasing others to focus on the most challenging and impactful vulnerabilities. These changes show that the industry is struggling to sort useful findings from noise while keeping costs sustainable. The same AI tools that help defenders also help attackers, which is the core asymmetry of this arms race. AI systems can now scan entire codebases, detect subtle patterns humans miss, and generate exploit code in days or even hours instead of months. 

Historically, exploiting a vulnerability could take years; now, exploits can emerge within 24 hours after discovery. This compression of the timeline means developers have less time to patch, attackers can automate exploitation, and low-skilled hackers gain advanced capabilities that were once reserved for elite teams. The result is a shrinking window between finding a flaw and it being weaponized. 

Organizations are responding with a mix of economic and structural measures. Some researchers argue that companies cannot simply “patch their way out of this” and must instead build infrastructure that makes many bugs irrelevant in practice. The industry is shifting toward “secure by default” designs, automated scanning in release candidates, and security-first development practices that reduce the number of exploitable weaknesses from the start. Google’s payout adjustments reflect a strategic shift to reward only the most impactful vulnerabilities, while smaller firms may struggle to keep up with rising costs and report volumes. 

The long-term issue is that vulnerability discovery is no longer a human-limited process but a machine-driven one, changing the balance of power in cybersecurity. AI exposes weaknesses faster than communities can respond, and the backlog of bugs now grows faster than it can be resolved. The winners will be those who treat security as continuous defense-in-depth, not as a one-time fix, and who build systems where most bugs are made irrelevant by design rather than by constant patching.
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WannaCry ransomware
cybersecurity leaks EternalBlue NotPetya attack NSA hacking tools Shadow Brokers Vulnerabilities and Exploits WannaCry ransomware

Shadow Brokers Mystery Remains One of Cybersecurity’s Biggest Unsolved Cases

 

dThe world of cybersecurity has witnessed countless data breaches and hacking incidents over the years, many of which remain unresolved despite extensive investigations. While several notorious cybercriminal groups and state-backed hacking operations have eventually been exposed, some of the most significant cyber mysteries continue to puzzle experts.

Among these unsolved cases, few are as intriguing as the story of the Shadow Brokers — a mysterious online group that shocked the cybersecurity community by releasing a cache of advanced hacking tools allegedly linked to the U.S. National Security Agency (NSA) before disappearing without a trace.

The group first emerged in the summer of 2016, a period already marked by heightened attention on cyberattacks connected to the U.S. presidential election. Shadow Brokers appeared on Twitter and directed users to a Pastebin post, tagging several media organizations in the process. However, the unusual method of communication meant many of those outlets likely never noticed the messages.

Those who followed the link encountered a document titled “Equation Group Cyber Weapons Auction — Invitation,” referring to the Equation Group, a sophisticated cyber operation widely believed to be associated with the NSA.

In the announcement, the hackers wrote, “!!! Attention government sponsors of cyber warfare and those who profit from it !!!! How much you pay for enemies’ cyber weapons?” They claimed to have breached the Equation Group and offered access to stolen cyber tools. The post included downloadable samples along with an encrypted archive that could supposedly be unlocked by the highest bidder.

Promoting the contents, the group stated, “Auction files better than Stuxnet,” referencing the malware deployed against Iranian nuclear facilities during a joint U.S.-Israeli cyber operation in 2007. The hackers demanded bids of at least one million Bitcoin.

The leak rapidly drew global attention. As cybersecurity experts examined the released tools, many concluded that the software was exceptionally advanced and likely originated from the NSA. This belief strengthened when researchers noticed similarities between the leaked tools and programs previously revealed through disclosures by former NSA contractor Edward Snowden.

Over time, it became apparent that the auction itself may never have been intended as a genuine sale. Months later, the Shadow Brokers publicly released many of the tools without receiving the requested payment. Their behavior often appeared contradictory. The group’s unusual and frequently broken English raised questions about whether they were deliberately disguising their identity or attempting to mislead investigators.

Despite attracting widespread media coverage, the group remained remarkably elusive. They communicated with journalists only once, granting a brief interview to Joseph Cox, now of 404 Media, during his tenure at VICE Motherboard. A decade later, the true identities behind the Shadow Brokers remain unknown.

At the time, journalists and researchers consulted former NSA personnel, some of whom speculated that a current or former agency insider could have played a role. Yet no individual has ever been formally charged for carrying out one of the most damaging intelligence-related cyber leaks in U.S. history.

One frequently discussed suspect was Harold T. Martin III, an NSA contractor arrested for removing classified materials from the agency. However, investigators faced a significant challenge with that theory: Shadow Brokers continued posting online after Martin had already been taken into custody. As a result, he has never been officially linked to the leaks through criminal charges.

A more widely accepted explanation among analysts suggests that the Shadow Brokers may have been a front created by a Russian intelligence operation designed to influence public perception and advance strategic objectives.

The consequences of the leak were profound. Among the exposed tools was EternalBlue, a collection of Windows zero-day vulnerabilities that enabled attackers to infiltrate systems, move laterally across networks, and spread malware automatically. Because zero-day vulnerabilities are unknown to software developers, they often remain unpatched and highly dangerous until discovered.

The leaked EternalBlue exploit later became the foundation for some of the most destructive cyberattacks ever recorded. North Korean hackers used it in the WannaCry ransomware outbreak, while Russian operators incorporated it into the NotPetya malware campaign. Although initially aimed at targets in Ukraine, NotPetya spread globally and is estimated to have caused around $10 billion in economic losses.

For organizations worldwide, the incident underscored a critical cybersecurity lesson: vulnerabilities stockpiled by intelligence agencies can eventually escape into the public domain, creating enormous risks for businesses and governments alike.

Even years later, researchers continue uncovering new insights from the leaked materials. One tool contained a list of project names, including an entry called Fast16 that carried the unusual note, “NOTHING TO SEE HERE — CARRY ON.”

Last month, cybersecurity researchers announced that they had successfully located and analyzed the project. Their investigation uncovered malware dating back to 2005 that was reportedly designed to manipulate software believed to be used by Iranian nuclear scientists, demonstrating that the Shadow Brokers leak continues to reveal new chapters in cyber espionage history.


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WolfSSL flaw
AI cybersecurity Anthropic Claude Mythos Preview Project Glasswing software vulnerabilities Vulnerabilities and Exploits WolfSSL flaw

Anthropic’s Project Glasswing Detects Over 10,000 Critical Software Vulnerabilities Worldwide

 

iArtificial intelligence company Anthropic has revealed that its cybersecurity initiative, Project Glasswing, has successfully identified more than 10,000 high- and critical-severity vulnerabilities across globally significant software systems since the program was introduced last month.

The initiative was designed as a defensive cybersecurity program aimed at strengthening critical software infrastructure worldwide. Through Project Glasswing, around 50 trusted partners receive early access to Claude Mythos Preview — an advanced AI model capable of autonomously discovering vulnerabilities in widely used software before malicious actors can exploit them.

According to Anthropic, 6,202 of the detected vulnerabilities were categorized as high or critical severity and affected over 1,000 open-source projects. Further review confirmed 1,726 of these findings as legitimate true positives, while 1,094 vulnerabilities were assessed as either high or critical in severity.

Among the major discoveries was a critical security flaw in WolfSSL identified as CVE-2026-5194, carrying a CVSS score of 9.1. The vulnerability could potentially allow attackers to forge certificates and impersonate legitimate services. Anthropic noted that the initiative has already contributed to 97 vulnerabilities being patched upstream along with the release of 88 security advisories.

"The relative ease of finding vulnerabilities compared with the difficulty of fixing them amounts to a major challenge for cybersecurity," Anthropic acknowledged. "Confronting this challenge successfully will make our software far safer than before."

The announcement comes amid a broader rise in AI-assisted vulnerability discovery, with software vendors releasing patches at an unprecedented pace. Microsoft recently indicated that the number of monthly security patches is expected to continue increasing over time.

Cybersecurity firm XBOW described Mythos Preview as "a major advance" that is "substantially better than prior models at finding vulnerability candidates" and "adept at analyzing source code with a security mindset." Researchers have also observed the model’s effectiveness in converting vulnerabilities into complete end-to-end attack chains.

Anthropic highlighted that the capabilities of Mythos Preview extend beyond vulnerability detection. In one reported incident, a banking partner participating in Glasswing used the AI model to identify and block a fraudulent wire transfer worth $1.5 million after a threat actor compromised a customer’s email account and attempted spoofed phone calls.

The company warned that AI models with capabilities similar to Mythos could become widely accessible in the near future, prompting a need for organizations to accelerate their patch management processes. Oracle has already transitioned to a monthly patch cycle to respond more quickly to critical security vulnerabilities.

"Network defenders should shorten their patch testing and deployment timelines," Anthropic said. "These include steps like hardening networks' default configurations, enforcing multi-factor authentication, and keeping comprehensive logs for detection and response."

Anthropic also announced the launch of its Cyber Verification Program, which allows verified security researchers to use its AI models without standard guardrails for legitimate cybersecurity activities such as penetration testing, vulnerability research, and red teaming. The move mirrors OpenAI’s Daybreak initiative, which enables defenders to work with GPT-5.5-Cyber for specialized security workflows.

Despite their advanced capabilities, models such as Mythos Preview and GPT-5.5-Cyber have not yet been publicly released due to concerns surrounding potential misuse and the absence of sufficient safeguards against large-scale abuse.

"Glasswing helps the most systemically important cyber defenders gain an asymmetric advantage," it pointed out. "However, there is an urgent need for as many organizations as possible to shore up their cyber defenses. We hope that our generally available models, and the new tools, resources, and research we're providing to accompany them, will support those organizations to improve their cybersecurity posture."
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Vulnerabilities and Exploits
Claude AI Google Ads Mac Users User Security Vulnerabilities and Exploits

Hackers Abuse Google Ads and Claude.ai Chats to Spread Mac Malware

 

Cybercriminals are once again abusing trust, and this time they are combining Google Ads with Claude.ai shared chats to push malware onto Mac users. The campaign targets people searching for terms like “Claude mac download,” where sponsored results appear to point to the legitimate claude.ai domain but actually lead to malicious installation instructions. Security researcher Berk Albayrak first identified the scheme, and confirmed that attackers are using the tactic in active campaigns. 

The attack works because it looks believable at first glance. Users click a sponsored search result, land on a public Claude chat, and see what appears to be an official “Claude Code on Mac” guide, sometimes even attributed to Apple Support. That page then tells them to open Terminal and paste a command. Instead of installing useful software, the command quietly downloads and runs malware on the victim’s Mac.

What makes the operation especially dangerous is the way it blends legitimate services with deception. The ad itself can show the real claude.ai domain, which helps the link look safe, while the malicious instructions are hidden inside Claude’s shared chat feature. In some variants, the payload is linked to MacSync-style infostealer behavior, aimed at harvesting browser credentials, cookies, and Keychain data. Researchers also reported that multiple malicious chats were being used, showing that the operators are testing and rotating infrastructure. 

The campaign is a strong reminder that search results and AI platforms are not automatically trustworthy just because they appear familiar. Attackers increasingly rely on “clickfix” tactics, where the victim is convinced to copy and run a command manually, bypassing many traditional download warnings. That user action becomes the infection point, making the social engineering as important as the malware itself.

Mac users should avoid sponsored search results when looking for software downloads and instead go directly to the official site by typing the address themselves. Any chat, guide, or support page that instructs users to paste Terminal commands should be treated with caution, especially if it claims to come from Apple or a well-known AI service. The broader lesson is simple: when an instruction asks you to run code on your own computer, pause and verify before acting.
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Vulnerabilities and Exploits
Administrative Rights Copy Fail Kernel Bug Linux Kernel Vulnerabilities and Exploits

Linux Copy Fail Vulnerability Puts Major Systems at Risk

 

A critical Linux kernel vulnerability known as Copy Fail is drawing urgent attention because it can let a local, unprivileged attacker gain root access on affected systems. Security researchers say the issue affects many mainstream Linux distributions and can be abused without network access, which makes patching and temporary mitigation especially important for administrators. Security experts note that the easiest fix is to update the kernel to the latest patched version. 

Copy Fail is tracked as CVE-2026-31431 and centers on the Linux kernel’s algif_aead module, part of the AF_ALG cryptographic interface. The flaw stems from an in-place optimization introduced in 2017 that can be combined with splice() to perform a controlled write into the page cache of a readable file. In practice, that means an attacker could target a setuid binary such as /usr/bin/su and use the modified cached copy to obtain elevated privileges. 

The vulnerability is serious because it has been verified on several major Linux environments, including Ubuntu, Amazon Linux, RHEL, and SUSE, with kernels built since 2017. CERT-EU says that at the time of its advisory, no distribution had yet shipped a fixed kernel package, even though the upstream fix had already been committed. That delay means many systems may remain exposed until vendors roll out updates.

For now, the main mitigation is to update to a patched kernel as soon as one becomes available. Until then, CERT-EU recommends disabling algif_aead and unloading the module where possible, since the exploit depends on that path. In containerized or multi-tenant environments, blocking AF_ALG socket creation through seccomp can provide an additional layer of protection.

System administrators should treat Copy Fail as a high-priority kernel issue and check whether their environments use affected kernel versions. Because the attack can alter the cached copy of a binary rather than the file on disk, basic integrity checks may not reveal the problem immediately. The safest approach is to patch promptly, apply interim mitigations, and verify that the vulnerable module is no longer active.
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Web Hosting
active exploitation cPanel SSH Keys Vulnerabilities and Exploits Web Hosting

Hackers Exploit cPanel Flaw to Gain Control of Thousands of Websites

 

Hackers are still aggressively exploiting a critical bug in cPanel and WHM, the widely used web hosting control software that powers countless websites across the internet. The flaw, tracked as CVE-2026-41940, lets attackers bypass the login screen and seize administrative access to affected servers without a password. Because cPanel is deeply embedded in shared hosting environments, a single compromised server can expose many unrelated websites at once. 

The scale of the problem is large. Security researchers say more than 550,000 cPanel servers may be vulnerable, while roughly 2,000 instances were believed to be compromised at the time of reporting, down from about 44,000 last week. That drop suggests some hosting providers and administrators have already begun cleaning up or blocking attacks, but the threat remains active and widespread. 

What makes the issue especially dangerous is how much control the bug gives to attackers. Once inside, criminals can manage website files, databases, SSL certificates, and other critical settings tied to every site hosted on the server. In practice, that means they can deface websites, install backdoors, steal data, or redirect visitors to malicious pages, all from the control panel intended for legitimate administrators.

The vulnerability has also shown signs of being abused before the public disclosure. One hosting provider reported seeing exploitation attempts as early as late February, well before the issue was officially disclosed and patched. The U.S. Cybersecurity and Infrastructure Security Agency added the flaw to its Known Exploited Vulnerabilities catalog, confirming that it is being used in real-world attacks and should be treated as an urgent patching priority. 

For site owners, the response needs to be immediate and practical. Systems should be patched to the latest cPanel and WHM releases, exposed login panels should be restricted where possible, and administrators should check for unauthorized users, modified files, suspicious SSH keys, and unexpected database changes. Hosting providers such as Namecheap, HostGator, and KnownHost have already taken emergency steps, including temporarily blocking access while they applied fixes. The wider lesson is that a single authentication-bypass flaw in a core admin tool can become a large-scale internet incident almost overnight.
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Windows Vulnerabilities
AI cybersecurity Kernel Security MDASH AI Microsoft security Patch Tuesday Remote Code Execution Threat Detection Vulnerabilities and Exploits Windows Vulnerabilities

MDASH AI Helps Microsoft Detect 16 Critical Windows Security Flaws


 

The company has reported that the MDASH framework, developed internally by Microsoft for agentic artificial intelligence, was instrumental in identifying 16 security vulnerabilities affecting core Windows networking and authentication components, including four critical vulnerabilities that can be exploited remotely. 

According to the discovery, which was addressed during Patch Tuesday's security rollout of May 2026, autonomous AI systems are not limited to the generation of code in defensive cybersecurity engineering. In addition to analyzing complex software environments, tracing insecure logic paths, and identifying exploitable weaknesses before threats can weaponize them, these tools are increasingly being used to analyze complex software environments. 

Microsoft's Autonomous Code Security team developed MDASH, which is currently being tested by a select number of customers in a private preview program. MDASH is now actively supporting internal security engineering operations and is part of the company's wider effort to integrate AI-driven vulnerability research into enterprise-scale software assurance and development processes. 

The MDASH framework is at the core of this initiative. It is an internally developed framework that works independently of any single language model while coordinating specialized AI agents tailored to specific vulnerability classes, a framework that is uniquely engineered for this purpose. By utilizing a combination of frontier-scale and distilled AI models, the platform distributes tasks across more than 100 purpose-built agents instead of relying on a conventional one-model scanning architecture. 

Using the system, Taesoo Kim, Microsoft's vice president of agentic security, enables the detection of end-to-end vulnerabilities by autonomously identifying suspicious code behavior, challenging each other's findings, and independently validating exploitability before escalated results that are confirmed. MDASH is an analysis pipeline that consists of multiple stages. 

After ingesting source code, MDASH constructs an internal threat model and maps the attack surface, and then dedicated agents conduct audits to identify possible vulnerabilities such as insecure logic, memory corruption, authentication vulnerabilities, and other exploitable conditions. In addition to eliminating false positives, a secondary layer of "debater" agents also performs adversarial reasoning workflows to verify technical validity and eliminate false positives. 

As a result of the correlation between semantically similar findings, consolidating overlapped detections, and providing proof-based validation, the framework is able to demonstrate that vulnerabilities can be exploited practically. Using Microsoft's architecture, Microsoft says complex security analysis can be performed using state-of-the-art reasoning models, distilled models for large-scale validation tasks, and a high-capability, independent counteranalysis model. 


Through layered reviews, Microsoft hopes to improve detection accuracy and reliability across enterprise-scale codebases including Windows. In addition to the TCP/IP networking stack, IKEEXT IPsec, HTTP.sys, Netlogon, DNS resolution mechanisms, and the legacy Telnet client, MDASH uncovered a number of deeply embedded Windows components that were susceptible to remote attack surfaces. These vulnerabilities underscore how wide a range of attacks can be conducted on modern operating systems. 

According to Microsoft, ten of the identified vulnerabilities affect kernel-mode components and six affect user-mode services. Under realistic deployment scenarios, most of these vulnerabilities are remotely accessible without authentication. In total, four vulnerabilities were rated Critical, including CVE-2026-338277, an unauthenticated use-after-free issue in tcpip.sys, and CVE-2026-338248, a remotely exploitable double-free issue in the IKEv2 protocol over UDP port 500. 

It is reported that MDASH demonstrated unusually high precision during validation exercises, in that all 21 intentionally seeded vulnerabilities were detected without generating false positives during internal testing. It was further stated by Microsoft that the framework recalled 96 percent of the five years of confirmed cases of the Microsoft Security Response Center for CLFS.sys and covered tcpip.sys in full, as well as scoring 88.45 percent on the CyberGym benchmark containing 1,507 real-world vulnerabilities, which is the highest score in the industry. 

The broader research initiative continues to be closely tied to Microsoft's offensive and defensive security engineering ecosystems. Currently, the platform is deployed across Microsoft's engineering environments and is currently being evaluated by limited customers through a private preview program. A team led by Autonomous Code Security worked in collaboration with Windows Attack Research and Protection specialists who specialized in advanced offensive Windows research to spearhead development efforts. 

A number of researchers involved in this project previously served as members of Team Atlanta, the team recognized for winning the DARPA AI Cyber Challenge using a system for discovering and patching vulnerabilities autonomously. The company stated that the implementation of autonomous auditing at an enterprise level can pose unique operational difficulties due to the proprietary nature of the Windows codebase and the absence of public training datasets. 

In addition, low-tolerance production environments prevent inaccurate detections from occurring. These constraints can be addressed by MDASH by providing extensible plugins capable of injecting highly specialized contextual knowledge into the analysis pipeline. These include kernel calling conventions, synchronization rules, interprocess communication trust boundaries, and file-system structures that are not reliably inferred by general-purpose models. 

A particular extension, developed for the Common Log File System (CLFS), generates triggering log artifacts from candidate findings automatically, allowing the framework to go beyond theoretical detection and provide proof-based vulnerability validation that engineering teams can use to remedy vulnerabilities directly. 

Using CVE-2026-33827 as an example of advanced flaws that conventional single-model AI systems routinely fail to identify, Microsoft highlighted that vulnerability. In order to address this vulnerability, Microsoft implemented a strict source and record route processing process that improperly managed a reference-counted Path object during the Windows IPv4 receive path.

It is possible that the affected function reused the same pointer under alternate execution flow conditions after releasing its owned reference through a dereference operation, therefore causing a race-driven use-after-free scenario in kernel memory. 

Due to the fact that the vulnerable code path processes attacker-controlled packet metadata and executes within an elevated networking context, a remote attacker could potentially exploit this flaw by sending specially crafted IPv4 packets containing SSRR options to their hosts. A Microsoft representative explained that the problem became significantly more dangerous as a result of the concurrency behavior of multiple independent cleanup subsystems that were capable of reclaiming the object before further reuse. 

According to the company, single-model artificial intelligence systems often fail to detect such vulnerabilities since ownership violations are not readily apparent locally and are instead dependent on correlating reference semantics, branching conditions, concurrency interactions, and analogous patterns spread across distinct code paths to determine the violation. 

The MDASH system was reported to have successfully analyzed the behavior of objects during their lifetimes, compared implementation inconsistencies elsewhere in the codebase, and assembled a coherent exploitation chain by using staged reasoning and adversarial verification through specialized agents. During Patch Tuesday in April 2026, the flaw was addressed. 

Furthermore, Microsoft disclosed CVE-2026-33824, a critical double-free vulnerability affecting IKEEXT, a key exchange service for IPsec authentication. Remotely accessible via UDP port 500, the vulnerability is capable of triggering against systems configured as IKEv2 responders, such as RRAS VPNs, DirectAccesss, Always-On VPNs, and hosts with IPsec security policies that govern inbound connections. There was a vulnerability caused by an ownership handling error during fragment reassembly, which caused a packet receive context to be duplicated by using shallow memory copy operations. 

A deterministic heap corruption condition was created within the LocalSystem svchost.exe process when teardown routines released the same memory region twice, resulting in reference to and assumption of ownership of the same heap allocation linked to a security realm identifier controlled by an attacker.

The vulnerability is particularly severe from a defensive perspective, as it only requires two crafted UDP packets without race conditions or precise timing requirements, making exploitation particularly easy. During analysis of the codebase, the company identified that the flaw extended across six separate source files, and that the vulnerability was triggered by subtle differences between ownership handling patterns that were incorrect and correctly implemented elsewhere.

Microsoft has stated that multiple file aliasing and lifecycle vulnerabilities are routinely evaded by conventional automated analysis because a single execution context does not expose the entire exploitation chain at once. MDASH's multi-agent debate and verification architecture is specifically credited for identifying those fragmented relationships and confirming the exploit path before publication. 

The issue was also patched as part of April 2026 Patch Tuesday. There is a notable shift in how large-scale software security auditing will evolve in enterprise environments with the emergence of MDASH. Modern operating systems are becoming increasingly complex and difficult to assess through traditional manual methods alone.

The Microsoft AI platform combines autonomous reasoning, adversarial validation, and exploit-focused analysis in a coordinated multi-agent framework, enabling AI to not merely serve as a productivity tool, but also to provide an operational security layer capable of detecting deeply buried vulnerabilities within critical infrastructure code. 

A growing number of threat actors are leveraging automation in offensive campaigns, and the company’s latest findings suggest that defensive research may become increasingly dependent on AI-driven systems capable of identifying exploitable weaknesses before they become operational.
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Vulnerabilities and Exploits
Cybersecurity Exim security flaw Exim vulnerability remote code execution Vulnerabilities and Exploits

Critical Exim Flaw Exposes Email Servers to Remote Code Execution Risk

 

A newly discovered security vulnerability in the widely used mail transfer agent Exim has raised serious concerns among cybersecurity experts, as attackers could exploit the flaw to potentially execute malicious code remotely on vulnerable email servers.

According to researchers, the vulnerability occurs due to improper memory handling during the TLS session shutdown process. The issue specifically affects Exim installations using GnuTLS configurations.

“This sequence of events can cause Exim to write into a memory buffer that has already been freed during the TLS session teardown, leading to heap corruption. An attacker only needs to be able to establish a TLS connection and use the CHUNKING (BDAT) SMTP extension.”

Security experts confirmed that all Exim versions starting from 4.97 through 4.99.2 are vulnerable. However, systems relying on OpenSSL or other TLS libraries are not affected, as the flaw only impacts builds compiled with USE_GNUTLS=yes.

The vulnerability was identified by Federico Kirschbaum, Head of Security Lab at XBOW, an autonomous cybersecurity testing platform, who reported the issue on May 1, 2026.

“During TLS shutdown, Exim frees its TLS transfer buffer – but a nested BDAT receive wrapper can still process incoming bytes and end up calling ungetc(), which writes a single character (\n) into the freed region,” Kirschbaum said. “That one-byte write lands on Exim's allocator metadata, corrupting the allocator's internal shape; the exploit then leverages that corruption to gain further primitives.”

XBOW described the flaw as one of the most severe vulnerabilities uncovered in Exim in recent years, noting that attackers require minimal server-side configuration to trigger the exploit successfully.

To address the issue, Exim developers released version 4.99.3 and urged administrators to upgrade immediately. The developers also clarified that no temporary workaround or mitigation is currently available.

“The fix ensures that the input processing stack is cleanly reset when a TLS close notification is received during an active BDAT transfer, preventing the stale pointers from being used,” Exim noted.

This is not the first major security concern involving Exim. Back in 2017, the platform fixed another critical use-after-free vulnerability, tracked as CVE-2017-16943, which allowed unauthenticated attackers to execute remote code using specially crafted BDAT commands and potentially take control of email servers.
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Windows Update Flaw
AI Infrastructure Security AI Security CVE-2026-7482 Cybersecurity Threats GGUF Exploit Ollama Vulnerability Remote Code Execution Vulnerabilities and Exploits Windows Update Flaw

Remote Exploitation Risk Emerges From Ollama Out-of-Bounds Read Flaw


 

Increasing reliance on large language model infrastructure deployed locally has prompted a renewed focus on self-hosted artificial intelligence platforms' security posture after researchers revealed a critical vulnerability in Ollama that could lead to remote attackers gaining access to sensitive process memory without authorization. 

CVE-2026-7482, a security vulnerability with a CVSS severity score of 9,1 describes an out-of-bounds read vulnerability that can expose large portions of memory associated with running Ollama processes, including user prompts, system instructions, configuration data, and environment variables, as a result of an out-of-bounds read. Because Ollama is widely used as a local inference platform for open-source large language models such as Llama and Mistral, the disclosure has raised significant concerns among artificial intelligence and cybersecurity communities.

By using their own infrastructure rather than using external cloud providers, organizations and developers are able to run AI workloads directly. There are approximately 170,000 stars on GitHub, over 100 million Docker Hub downloads, and deployment footprints on nearly 300,000 servers accessible through the internet, which highlight the growing security risks associated with rapidly adopted artificial intelligence ecosystems as well as the sensitive operational data they process. 

Cyera has identified the vulnerability, dubbed Bleeding Llama, to originate from an insecure handling of GGUF model files within Ollama, in which the server implicitly trusts tensor dimension values embedded inside uploaded models without performing adequate boundary validations. Through this design weakness, an application can manipulate memory access operations during model processing by creating specially crafted GGUF files, forcing it to read data outside the application's intended memory buffers and incorporating fragments of sensitive runtime information into model artifacts generated by the application.

It is clear that the underlying problem is linked to the GPT-Generated Unified Format (GGUF), which is widely used to package and distribute large language models that can be efficiently executed locally. Similar to PyTorch's .pt and .pth models, safetensors, and ONNX models, GGUF enables developers to store and execute open-source models directly on local computers without the need for external resources. 

The vulnerability is identified as a result of the manner Ollama processes these files during model creation, specifically by using Go's unsafe package within a function known as WriteTo(). The implementation inadvertently exposes the heap to out-of-bounds reads when malicious tensor metadata is supplied because it relies on low-level memory operations that bypass standard language safety protections. 

It is possible to exploit this vulnerability by crafting a GGUF file with intentionally oversized tensor shape values and sending it to an exposed Ollama instance via the /api/create endpoint in an attack scenario. By manipulating dimensions, the application is forced to access memory regions outside the allocated boundaries during parsing and model generation. As a result, sensitive information contained within the Ollama process space is unintentionally disclosed. 

According to researchers, exposed memory may contain environment variables, authentication tokens, API credentials, system prompts, as well as portions of concurrent user interactions processed by the same instance. CVE-2026-7482 functions differently from conventional exploitation techniques, as it is a silent disclosure mechanism preventing data leakage without crashes, visible failures, or immediate forensic indicators, as opposed to conventional exploitation techniques. 

In internet-accessible deployments, the attack chain itself is considered relatively straightforward, significantly reducing the difficulty of remote exploitation. In order to manipulate Ollama into harvesting unintended memory regions during parsing and artifact generation, attackers can upload malicious GGUF models via the unauthenticated /api/create endpoint. These manipulated tensor dimensions then coerce Ollama into uploading the malicious model. 

An artifact containing sensitive process data can then be exported through the unauthenticated /api/push endpoint, allowing covert exfiltration of stolen information. According to security researchers, since many Ollama instances remain directly exposed to the Internet without adequate access restrictions, the vulnerability poses a particularly serious risk to enterprises and developers using local AI infrastructure assuming self-hosted deployments provide a higher degree of data isolation. 

Analysts warn that the “Bleeding Llama” vulnerability significantly increases the risks associated with self-hosted artificial intelligence infrastructure since unauthenticated attackers will have direct access to the active memory space of the Ollama process without the need for prior access or user involvement. 

In combination with the widespread adoption by enterprises and developers of the platform, the simplicity of exploitation transforms the issue from a single software defect into a large-scale exposure concern for organizations whose sensitive workloads rely on locally deployed language models. In contrast to conventional vulnerabilities causing service disruption, memory disclosure flaws of this nature are capable of silently compromising valuable operational and proprietary data for extended periods of time. 

A research study indicates that attackers could potentially extract confidential model weights, allowing for intellectual property theft or reconstruction of customized AI systems internally, as well as gathering sensitive prompts, business data, and user inputs processed by active models. 

In addition to infrastructure details and authentication tokens, exposed memory may reveal API credentials, runtime configuration information, and API credentials that could facilitate further network compromises. As well as the immediate technical risks, such incidents are also likely to adversely affect organizations increasingly integrating artificial intelligence systems into critical operations, especially those where privacy and local data control are important components of their deployments. 

Security teams across the industry have actively tracked this issue despite the absence of an official CVE identification number, which initially complicated the vulnerability disclosure process. According to defenders, organizations should prioritize rapid mitigation strategies, including immediately upgrading to patched Ollama releases once they are available, limiting public network exposure, implementing strict firewall and access control policies, and ensuring that the service operates under least privilege conditions to reduce access after a compromise has occurred. 

Further, security professionals recommend that network anomalies be monitored continuously, infrastructure audits for misconfigurations be conducted, and deployment within isolated or segmented networks in highly sensitive environments to reduce the attack surface of internet-accessible artificial intelligence systems. 

Furthermore, Striga researchers have identified two separate vulnerabilities that can be chained to result in persistent code execution within the Windows implementation of Ollama, compounding the disclosure surrounding "Bleeding Llama". Researchers have determined that the Windows desktop client is automatically launched during login through the Windows Startup folder and listens locally at 127.0.0.1:11434. 

After checking for updates from the /api/update endpoint periodically, the pending installers are executed the next time the application is started. It is characterized by a combination of a missing signature verification flaw - CVE-2026-42288 - and a path traversal vulnerability - CVE-2026-42249 - both of which have been assigned CVSS scores of 7.7.

According to researchers, the installer signatures are not validated before execution and staging paths are constructed directly from HTTP response headers without proper sanitization, enabling malicious files to be written to locations controlled by the attacker. The flaws may allow arbitrary executables to be silently deployed and executed during system login in scenarios in which an adversary could manipulate update responses, including redirecting the OLLAMA_UPDATE_URL configuration to a controlled HTTP server, while automatic updates remain enabled by default.

 The signature verification issue alone may allow temporary code to be executed from the staging directory, but when combined with a path traversal weakness, persistence can be achieved by writing payloads outside the expected update path, preventing subsequent legitimate updates from overwriting them. 

Ollama for Windows versions 0.12.10 through 0.17.5 are affected by this vulnerability and should be disabled automatically by Microsoft. Users are advised to remove Ollama shortcuts from the Windows Startup directory until patches can be made available. 

A broader security challenge is emerging across the rapidly evolving artificial intelligence ecosystem, which is being increasingly challenged by convenience-driven deployment models colliding with enterprise-grade security expectations as Ollama vulnerabilities develop in scope. 

In response to organizations' increasing adoption of self-hosted large language model infrastructure for the purposes of retaining greater control over sensitive data and inference workloads, researchers warn that insufficient hardening, exposed interfaces, and insecure update mechanisms can result in locally deployed AI environments becoming high-value attack targets. 

As a result of memory disclosure flaws, unauthenticated attack paths, and weaknesses within update workflows, AI infrastructure is becoming increasingly attractive to malicious actors looking to gain access to proprietary models, credentials, and operational intelligence, both opportunistic and sophisticated. 

Several security experts maintain that artificial intelligence platforms cannot be considered experimental development tools operating outside the traditional security governance framework, but rather need to be integrated into the same rigorous vulnerability management, network segmentation, monitoring, and software lifecycle practices that are used for critical enterprise systems.
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Vulnerabilities and Exploits
Cisco CVSS DoS Server Software Vulnerabilities and Exploits

Cisco Warns of Network Management Flaw That Can Force Systems Offline Through Remote DoS Attacks




Cisco has disclosed a high-severity vulnerability affecting its network management platforms, Cisco Crosswork Network Controller and Cisco Network Services Orchestrator, which could allow remote attackers to crash vulnerable systems by exhausting their available connection resources.

The security issue, tracked as CVE-2026-20188, carries a CVSS score of 7.5. According to Cisco, the flaw can be exploited remotely without authentication, meaning an attacker does not need valid credentials or prior access to interfere with affected servers.

At the center of the problem is how the platforms manage incoming network connections. Cisco explained that the affected software does not properly control or restrict the rate of connection requests sent to the server. Because of this weakness, a malicious actor can continuously bombard the system with repeated requests until all available connection resources are consumed.

Once the systems run out of resources, both Cisco CNC and NSO can stop responding entirely. Administrators may lose access to management interfaces, while network operations that depend on these platforms can experience abrupt disruption.

Unlike temporary service slowdowns, the systems do not automatically recover after the overload occurs. Cisco stated that administrators must manually reboot the affected platforms to clear the exhausted resources and restore normal operations.

The company internally tracks the issue under Bug ID CSCwr08237. Cisco said the flaw originates from the connection-handling mechanisms used within both products.

Denial-of-service vulnerabilities of this kind are often disruptive because they target system availability rather than data theft. In enterprise environments, orchestration and network control platforms are responsible for coordinating automated processes, monitoring infrastructure, and managing service delivery across large networks. If these systems become unreachable, organizations can temporarily lose visibility into network operations and automated workflows.

Cisco is urging organizations using these products to immediately review their software versions and determine whether their environments are exposed.

For Cisco Crosswork Network Controller, the vulnerability affects version 7.1 and all earlier releases. Cisco confirmed that version 7.2 is not impacted, making upgrades necessary for organizations still operating older deployments.

The issue also affects several release branches of Cisco Network Services Orchestrator. Systems running version 6.3 or earlier remain vulnerable and require immediate updates. Cisco further confirmed that the flaw exists within the 6.4 release branch, although the issue was corrected beginning with version 6.4.1.3. Organizations operating NSO version 6.5 or later are not affected.

Cisco discovered the vulnerability internally while handling a routine Technical Assistance Center support case. At this time, the company’s Product Security Incident Response Team said it has not observed public proof-of-concept exploit code or evidence showing active attacks targeting the flaw.

Even so, the company warned that customers cannot rely on temporary mitigations to reduce exposure. Cisco stated there are currently no workarounds capable of preventing the resource exhaustion issue without affecting legitimate system functionality. Because of this, upgrading to patched software releases remains the only available method for fully securing vulnerable environments.

Security professionals have increasingly warned that resource exhaustion attacks continue to pose operational risks for enterprises because they can interrupt business-critical infrastructure without requiring sophisticated intrusion techniques. Attackers often exploit weaknesses in traffic handling, connection management, or request validation to overwhelm services and force outages.

Cisco is advising affected customers to schedule maintenance windows and deploy the recommended updates as quickly as possible to reduce the risk of service interruptions and administrative lockouts.

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Windows antivirus flaw
Chaotic Eclipse researcher Microsoft Defender vulnerability Red Sun exploit Vulnerabilities and Exploits Windows antivirus flaw

Microsoft Defender “Red Sun” Flaw Raises Questions Over Antivirus Reliability and Disclosure Practices

 

Microsoft Defender Antivirus, widely used as the default protection layer for Windows systems, is facing scrutiny after a newly disclosed vulnerability suggested it may fall short in certain scenarios. Despite its role as a frontline defense against malware, recent findings indicate that the tool might not always behave as expected—and critics say Microsoft has not shown urgency in addressing the concern.

A cybersecurity researcher operating under the name Chaotic Eclipse revealed the flaw, calling it “Red Sun.” The researcher shared that a proof-of-concept (PoC) demonstrates how attackers could potentially bypass Defender’s protections. They also warned that threat actors may already be experimenting with the vulnerability.

The issue appears to originate from how Defender processes suspicious files tagged with a “cloud” marker. Under certain circumstances, the antivirus may restore or rewrite these files back to their original locations. According to the PoC, this behavior could be manipulated to overwrite critical system files, potentially allowing privilege escalation.

"I think anti-malware products are supposed to remove malicious files not be sure they are there but that's just me," remarked Chaotic Eclipse.

Earlier in the month, the same researcher disclosed another zero-day vulnerability named BlueHammer. He claimed that Microsoft Security Response Center did not consider it a major threat, prompting him to release the PoC publicly. In a follow-up discussion on Red Sun, Chaotic Eclipse said his interactions with the MSRC team have worsened, accusing Microsoft developers of unprofessional conduct.

"It was soo bad at some point I was wondering if I was dealing with a massive corporation or someone who is just having fun seeing me suffer but it seems to be a collective decision," he said.

The researcher further alleged that Microsoft’s security division has, at times, discouraged independent vulnerability reporting rather than supporting it. He also pointed to previous cases where other researchers voiced dissatisfaction with how MSRC handled their disclosures.

Despite the controversy, Red Sun is being treated as a valid security concern within the cybersecurity community. Analysts have also flagged possible real-world exploitation attempts targeting BlueHammer, Red Sun, and another vulnerability referred to as UnDefend.

Chaotic Eclipse identified the Red Sun flaw while reviewing fixes tied to CVE-2026-33825, which was addressed in Microsoft’s latest Patch Tuesday update. Additional patches may follow as further related issues come to light, even as discussions continue around Microsoft’s response to vulnerability reports.

Meanwhile, some experts suggest users consider third-party antivirus tools instead of relying solely on Microsoft Defender, though opinions differ. The researcher himself mentioned a preference for Bitdefender Antivirus Free, describing it as a lightweight solution built on a widely adopted malware detection engine.
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Vulnerabilities and Exploits
PhantomCore Russian Firms TrueConf Ukrainian Hackers Vulnerabilities and Exploits

PhantomCore Exploits TrueConf Flaws to Breach Russian Networks

 

A pro-Ukrainian hacktivist group known as PhantomCore has been exploiting vulnerabilities in TrueConf video conferencing software to infiltrate Russian networks since September 2025. According to a Positive Technologies report, the attackers chained three undisclosed flaws in TrueConf Server, allowing them to bypass authentication, read sensitive files, and execute arbitrary commands remotely. Despite patches being released by TrueConf on August 27, 2025, the group independently reverse-engineered these issues, launching widespread attacks on Russian organizations without relying on public exploits. 

The vulnerabilities include BDU:2025-10114 (CVSS 7.5), an insufficient access control flaw enabling unauthenticated requests to admin endpoints like /admin/*; BDU:2025-10115 (CVSS 7.5), which permits arbitrary file reads; and the critical BDU:2025-10116 (CVSS 9.8), a command injection vulnerability for full OS command execution. This exploit chain grants attackers initial foothold on vulnerable servers, facilitating lateral movement and persistence within victim environments. 

PhantomCore's operations highlight their sophistication, as they maintain stealth for extended periods—up to 78 days in some cases—while targeting sectors like government, defense, and manufacturing. PhantomCore's tactics extend beyond TrueConf exploits, incorporating phishing with password-protected RAR archives containing PhantomRAT malware, a shift from earlier ZIP-based methods. Positive Technologies noted over 180 infections from May to July 2025 alone, peaking on June 30, with at least 49 hosts still under attacker control as of early 2026. The group's pro-Ukrainian affiliation aligns with geopolitical motives, focusing exclusively on Russian entities amid ongoing cyber-espionage waves. 

Organizations running TrueConf face heightened risks if unpatched, as attackers evolve tools to evade detection and conduct large-scale breaches. Immediate mitigations include applying the August 2025 patches, monitoring admin endpoints and command logs for anomalies, and segmenting video conferencing servers from core networks. Enhanced defenses against lateral movement, such as network micro-segmentation and behavioral analytics, are crucial to counter PhantomCore's persistence. 

This campaign underscores the dangers of unpatched collaboration tools in sensitive environments, where private zero-days can fuel nation-aligned hacktivism. Russian firms must prioritize vulnerability management and threat hunting, as PhantomCore's adaptability signals ongoing threats into 2026. By staying vigilant, defenders can disrupt such stealthy intrusions before they escalate to data exfiltration or sabotage.
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Vulnerabilities and Exploits
Anthropic AI Mythos Security Risk Threat Intelligence Vulnerabilities and Exploits

Anthropic's Mythos: AI-Powered Vulnerability Discovery Forces Cybersecurity Reckoning

 

Anthropic’s Mythos is less a single “hacker AI” than a signal that cybersecurity is entering a new phase. The real reckoning is not that one model can break everything at once, but that software weakness will be found faster, cheaper, and at greater scale than defenders are used to. Anthropic’s own testing says Mythos can identify and chain serious vulnerabilities across major operating systems and browsers, which is why the company withheld public release and limited access to select organizations for defense work.

That shift matters because security teams have long relied on human pace. Vulnerability research, exploit development, patch validation, and incident response usually move slower than attackers would like; Mythos compresses that timeline. Anthropic says the model can uncover subtle, long-standing flaws, including issues that survived years of automated testing and human review. That does not mean every discovered flaw becomes an immediate catastrophe, but it does mean the window between “bug found” and “weaponized” could shrink dramatically.

Threat analysts believe that AI’s biggest cybersecurity impact may come from existing tools, not only from frontier models like Mythos. Even before Mythos, attackers and defenders were already using AI agents to generate code, search for weaknesses, and automate parts of exploitation and remediation. So the danger is not a sudden cliff where the world changes overnight; it is a steady acceleration that makes old security assumptions look outdated. In that sense, Mythos is a spotlight, not the whole show. 

A second layer of concern is organizational. Anthropic is giving Mythos to more than 40 companies and several security-focused groups so they can test their own systems and harden critical software. That defensive access may help, but it also reveals an uncomfortable reality: the same capabilities that strengthen security can also lower the barrier for misuse if they spread beyond controlled settings. This creates pressure on companies to treat AI as part of the threat model rather than as a productivity add-on. 

Threat analysts ultimately argues for a change in mindset. Security can no longer be an afterthought or a compliance layer added at the end of development. If AI can find and chain vulnerabilities at machine speed, then “secure by design” has to become the default, with better code practices, stronger testing, faster patching, and tighter controls around high-risk AI systems. Mythos may not trigger the exact cybersecurity crisis many people imagined, but it does force a more serious one: software defense must evolve as quickly as software attack.
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