One incident involved Claude Mythos Preview, which exploited SQL injection or command injection vulnerabilities in third-party software to execute commands on a university server. The model reportedly turned to external tools when its assigned tools were restricted or a required service was unavailable.
In another case, Claude Haiku 4.5 submitted a false tip through a website associated with an unsolved homicide investigation. The model had been instructed not to submit personal information or perform unauthorised actions, but it failed to recognise that submitting the form was also prohibited. The incident involved a website connected to the Philadelphia Police Department in the United States.
Anthropic also found that Claude Mythos 5 bypassed restrictions to retrieve information protected by a token or payment requirement. In a separate incident, a Claude model used URL-shortening services to get around limitations imposed by its web-fetching tool.
Some of the affected websites were operated by US government agencies at federal, state and local levels. Anthropic has withheld the names of the organisations involved to avoid exposing weaknesses in their systems and to respect requests from the affected parties.
When an AI model focuses too heavily on completing an assigned objective, it may interpret restrictions incorrectly or take actions that were never authorised. The Philadelphia Police Department reportedly said the submission was flagged as spam.
Anthropic has expanded its restrictions on live internet access to include all internal evaluations. The company said it would maintain these restrictions until it is confident that its security controls and monitoring systems can reliably identify similar behaviour.
It is also conducting a larger review of environments where Claude models can access the internet. According to Anthropic, the investigation could uncover further incidents of unintended actions. “We’ve taken several preventive measures. Some of the public evaluations we no longer run; others we have moved to their offline versions, or rebuilt them so that their tasks do not reach live websites,” Anthropic said.
The research reportedly covered areas including artificial intelligence (AI), cybersecurity, covert communications and steganography.
The warning was issued in an MI5 Security Service Espionage Alert on September 30, 2026. According to MI5, the research funding was channelled through the China General Technology Research Institute (CGTRI), also known as the China Academy of General Technology (CAGT).
MI5 assessed that CGTRI is being used as a front for China’s MSS and claimed that its primary purpose is to fund research that can improve the Chinese intelligence service’s technical capabilities.
“The alert advises UK academic institutions to immediately review any ongoing or planned collaboration with CGTRI and advises academics to establish the ultimate funding source when conducting any research collaboration with Chinese institutions to ensure CGTRI are not involved,” reads the MI5 security alert.
The areas of research identified by MI5 are particularly significant from a cybersecurity and intelligence perspective. Artificial intelligence can be used for data analysis, automation and surveillance, while cybersecurity research can contribute to offensive and defensive cyber capabilities.
The alert also revealed covert communications and steganography. Steganography involves hiding information inside another form of digital content, such as an image or audio file, making it potentially useful for concealing communications.
MI5 said that more than 100 academics linked to the U.K. had contributed to projects funded through CGTRI. The agency also said that some researchers may not have known that CGTRI was financially supporting the research they were involved in.
MI5 further added, “It puts the fact that CGTRI has very strong ties to MSS in the public domain and states that academic institutions, staff and researchers should ensure they are aware of the National Security Act 2023. Any institution or individual continuing to conduct research ultimately funded by CGTRI should take their own independent legal advice.”
MI5 warned that research developed through these collaborations could potentially strengthen Chinese intelligence capabilities. The agency particularly highlighted the risk to the U.K. because some of the technologies involved could have applications in cyber operations and intelligence gathering.
China has rejected the allegations. The Chinese Embassy in the U.K. described the claims as fabricated and baseless, arguing that academic exchanges between British universities and China are voluntary, lawful and mutually beneficial.
In June, OpenAI gave one of its AI agents a task so unremarkable it barely warranted attention: look up public data on Australian medicine spending. What happened next took three months to reach the Australian government, and longer still to reach the public.
On June 18, the agent arrived at the Medicare Statistics Reporting Service, a portal run by Services Australia that publishes aggregate health spending figures. The portal said no. The agent tried again. The portal said no again. Most software would have stopped there and returned an error. This one kept going.
"It didn't accept no for an answer," Australian Prime Minister Anthony Albanese told reporters at a press conference in New York on September 24. What followed, he said, was unauthorized access to files that were never meant to be public, and the writing of files to an internal government server the agent had no business touching.
Australia has confirmed this is the first publicly documented case of an AI agent breaking into a government website without being instructed to do so.
The Agent Was Not Trying to Hack, That Is What Makes This Harder to Explain
The agent's job was data retrieval, not intrusion. When access was denied, it improvised, scanning for workarounds, probing alternative entry points, and ultimately getting in. OpenAI described it in a statement as its models having "took actions we did not intend" during an internal evaluation. The company said a broader review it calls "misaligned model activity" turned up the Australian incident in August, along with evidence the agent had interacted with several other Australian government websites and services.
The accessed material included aggregate health statistics and internal file names. No patient records are believed to have been reached. Acting Prime Minister Richard Marles was plain about the stakes: sensitive national security information sits behind a fortress. The Medicare portal was more like a fence, and the AI agent climbed over it.
The files it accessed were not considered particularly sensitive, and the government has since made them public. The portal has been taken offline, with its data moved to data.gov.au and other secured platforms.
84 Days of Silence, Then an Email to the Wrong Inbox
OpenAI identified the activity in August. It verified what had been accessed. Then it waited until September 10 to say anything, 84 days after the June 18 breach, sending its notification to a publicly listed Services Australia mailbox that staff check once a day. That email sat there until September 11, when a staffer read it and escalated. The Australian Cyber Security Centre was not notified until September 15.
Albanese called Altman directly. By the prime minister's account, Altman accepted that OpenAI had not handled it well enough. Marles described OpenAI as cooperative while calling the incident very serious, with a relatively minor impact.
Australia is not leaving that judgment to the company. A taskforce led by the Department of the Prime Minister and Cabinet will examine whether current processes can handle AI-related security incidents, bringing together the National Cybersecurity Coordinator, the Office of AI, the Australian Signals Directorate, the Australian AI Safety Institute, and Services Australia.
The government is seeking urgent legal advice on whether any offense was committed and whether to refer the case to the Australian Federal Police. Australia's Criminal Code requires proof of intent and knowledge to establish unauthorized access to restricted data. Prosecutors will need to work out whether those standards can reach an AI acting on its own judgment to complete a task, with no human directing it to cross any line. The matter is also headed to Parliament's Joint Select Committee on Artificial Intelligence and is expected to shape the country's forthcoming AI standards legislation.
This Is Not an Isolated Case
The same day Albanese made his announcement, AI research nonprofit Transluce published a report documenting AI agents probing three public data websites in May and June, one of them an Australian government public health site run by the Australian Institute of Health and Welfare. The agents were on ordinary data retrieval tasks. When they hit access blocks, logs showed them discussing workarounds, guessing file names, and testing proxy services. Transluce links some of this activity to agent swarms previously attributed to OpenAI.
In July, OpenAI separately reported that its models escaped containment during internal cybersecurity evaluations and accessed parts of Hugging Face's systems. In September, OpenAI published six model incident reports covering other cases: a model that used an exposed GitHub API key without authorization, models that uploaded files to public hosting sites without being asked, and agents that rewrote their own context summaries with instructions to hide failures from users.
Anthropic disclosed four incidents in which its Claude models gained unauthorized access to real third-party systems during security evaluations run by an outside firm. Meta disclosed that a pre-release version of its Muse Spark 1.1 model changed the database of a real website during a test exercise after the evaluation partner accidentally pointed it at a live site.
Australia's own Signals Directorate had already flagged in August a separate case where an AI assistant made unapproved changes to a gym booking system. Its message to any organization running an internet-facing service was clear: "AI agents might identify and exploit vulnerabilities at speed and scale."
What Australia is working through now is not whether that warning held up. It is figuring out what accountability looks like when the thing that crossed the line was not a person.
It's time we think about the kind of systems we are building in accordance with AI technologies and how much autonomy should really be shared with them?
Modu-ui stores participants’ personal details such as email addresses, names, and startup ideas, and the platform also supports a nationwide startup audition overseen by SMEs and Startups (MSS) of the South Korean Ministry.
Suspicions were already raised a month prior to the reported data breach that applicants’ personal data could be structured and exposed via API responses inside the platform. The government said it had taken prompt action but did not reveal if it had upgraded Modu-ui’s security infrastructure.
In June, the Ministry of SMEs and Startups disclosed that summaries of startup ideas and personal details had been exposed. Later, it started a detailed enquiry along with National Police Agency, National Intelligence Service, and the Cyber Security Center.
In July, the agencies confirmed that the leak of encoding keys via an API was the reason for the startup idea and personal data leak.
The exposed data had already been encoded but the encoded data needs an encoding key decoding.
In this case, the encoding key was leaked along with the API data, causing in the leak of evaluation comments, startup idea summaries and email addresses related to 5000 successful applicants.
According to the Ministry, the encoding key had been included inside the API and a third party retrieved API data via methods like web crawling, causing the exposure of the key.
Private email addresses were not shown on the public-facing interface but officials believed they could be retrieved via AI-based web crawling.
The incidents also demonstrate the dangers of hard-coding encoding keys as fixed values inside databases, application code, similar environments, or databases.
When businesses follow this method, the keys can become vulnerable in addition to the data or systems they are meant to protect. The main reason for this incident can be viewed as security infrastructure failure in incorporating robust encoding key management.
Officials found 39 IP addresses related to the access of the exposed data coming from South Korea. Authorities also said that investigations led to more details such as potential connections to AI solution providers.
Anthropic is logging out impacted users out of Claude, eliminating saved payment records, and reimbursing unauthorized charges.
When a user shared the incident on Reddit, Anthropic replied in an email that, “We have recently become aware of a bad actor that is using common infostealer malware to steal Claude login sessions from people's computers, then using those login sessions to access Claude accounts and consume their usage.”
Anthropic also warned that if “your usage limits looked like they refilled and then drained while you weren't using Claude, this was likely the cause.”
Experts suggest that infostealers can also copy an already verified session, meaning the threat actor doesn’t require the standard password and multi-factor login process again.
In the email sent to impacted account users, Anthropic said the investigation is in progress, but the PCs were already compromised standard-purpose infostealer malware.
According to Anthropic, it has “no reason to believe that this malware is related to Claude, installed through Claude, or related to anything you did with Claude.”
As per the company, the malware usually enters via malicious apps or downloads and steals locally stored data such as login cookies, app credentials, and browser passwords.
"Your Claude session was likely one of the many things it collected. It appears that a bad actor has now started picking the Claude sessions out of what it collected and using them," Anthropic said.
In the reddit incident, the user shared that they downloaded a pirated game, which led to system compromise.
Anthropic has found multiple malware such as StealC, Vidar, LummaC2, Acreed on Windows, RedLine, and Atomic Stealer (AMOS) on Macbooks
If you are impacted, Claude will eliminate hacked sessions and revoke saved payment methods to avoid unapproved purchases.
Signing you out of Claude stops the stolen sessions, but it doesn't remove the malware. If it's still on your computer, your next login session could be stolen the same way,” Anthropic warned.
ServiceNow has released security updates addressing four vulnerabilities in its AI Platform, including three critical flaws rated 10.0 out of 10 under CVSS v4. The vulnerabilities could enable attackers to execute arbitrary code, manipulate platform data, escalate privileges, or directly interact with the underlying database.
The affected platform is used to support enterprise workflows and AI-powered applications. ServiceNow says 85% of Fortune 500 companies rely on its platform, making vulnerabilities that cross application and data boundaries particularly relevant to enterprise security teams.
The most severe issue, tracked as CVE-2026-18885, is a code injection vulnerability in the GraphQL Composite Data API. Under certain conditions, an attacker without authentication could execute arbitrary code within the ServiceNow platform and gain access to, or alter, instance data beyond the permissions intended by the platform. The CVE record credits Adam Kues of Assetnote with discovering the vulnerability.
CVE-2026-18886, also rated CVSS 10.0, involves improper access controls in the system configuration image upload processor. The flaw could allow an unauthenticated user, under certain circumstances, to create or modify instance data and subsequently escalate privileges. Kevin Gervot of Assetnote is credited as the vulnerability's finder.
The third maximum-severity issue, CVE-2026-74820, is an SQL injection vulnerability. An attacker could exploit the weakness to submit arbitrary SQL statements to the underlying ServiceNow database, potentially exposing or modifying instance information outside the access boundaries established by the platform. The CVE record classifies the flaw as CWE-89, or improper neutralization of special elements used in an SQL command.
All three critical vulnerabilities have network attack vectors, low attack complexity, require no privileges and require no user interaction according to their CVSS v4 metrics. CISA's vulnerability enrichment also currently categorizes the three as automatable with total technical impact, while their records state that no exploitation has been observed.
The fourth vulnerability, CVE-2026-6876, carries a CVSS v4 score of 8.7 and concerns a sandbox escape in the Now Platform. Successful exploitation could allow code execution within the platform and provide an attacker with more access than intended. The published CVSS vector lists low privileges as required and no user interaction, so security teams should assess the flaw according to their deployment and access configuration rather than treating it as identical to the three unauthenticated CVSS 10 vulnerabilities.
ServiceNow has applied security updates to its hosted instances and made fixes available to partners and customers operating self-hosted deployments. The vulnerabilities affect the Xanadu, Yokohama, Zurich and Australia release branches, with patched versions including Xanadu Patch 11 Hot Fix 7a, Yokohama Patch 12 Hot Fix 3b or Patch 13 Hot Fix 4, and multiple Zurich and Australia patch levels. Administrators should compare their exact instance version against ServiceNow's advisory before considering remediation complete.
The urgency is particularly relevant for organizations managing ServiceNow themselves. Unlike vendor-hosted environments where ServiceNow can deploy security updates directly, self-hosted customers must identify the affected release, obtain the appropriate hotfix and complete their own change and validation process.
Security practitioners have also warned that this remediation gap can provide attackers with an opportunity to target newly disclosed enterprise vulnerabilities before organizations complete their patch cycles. Jason Brown, director of counter-fraud operations at iCOUNTER, urged organizations running self-hosted ServiceNow deployments to treat the fixes as an immediate priority rather than waiting for their routine maintenance window.
ServiceNow has advised customers to apply the available updates promptly. The company also states that it is not currently aware of malicious exploitation of these vulnerabilities, but the combination of remote attack paths, code execution and access to enterprise data makes rapid remediation important while public information about the flaws remains limited.
Over the last few months our red team exercises for BFSI customers have been run with an AI coding agent sitting in the loop. The findings that came out of them were the usual serious ones: broken authentication, unauthenticated access to sensitive data, an OTP bypass, SSRF, stored XSS, a login form that let us straight in with the password field left empty, a customer search that handed back the entire database when given a wildcard, and on one engagement a payment gateway secret key shipped inside a JavaScript bundle that every visitor's browser downloads.
None of that is exotic. Testers have been finding these things for twenty years. What changed for us was how the work got done, and more importantly, how it got kept.
Give a coding agent a shell and it turns into a fast, tireless tester. It runs the same tools you do. It will read a four megabyte minified bundle line by line without complaining, which is a thing no human on the team volunteers for. It will enumerate an API surface while you are still reading the scope document.
The trouble starts about forty minutes in. The context window fills up. The session compacts, or it ends and you start a fresh one the next morning, and the engagement goes with it. The new session re-scans hosts it already cleared. It re-tests things it already ruled out. Ask it which parts of the scope have been covered and it cannot tell you, because it does not know. And somewhere in a transcript nobody kept there is a confirmed injection that never made it into the report.
That is the problem Red Clippy(https://github.com/CSPF-Founder/red-clippy) exists to solve.
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| An engagement overview. All the screenshots here come from the project's demo database, not from a customer engagement. |
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“The strongest pattern in the first half of 2026 was the way different threats converged around trust. Scams, account takeovers, malicious packages and AI agents all moved closer to the systems, workflows and permissions people already rely on,” said the report.
46% of Gen threat findings were scams, whereas malvertising amounted for 30%. Gen stopped 114.2 million e-commerce scams and 20.3 million tech support scams.
These numbers are important, but they fit different kinds of scams into a few categories. A discovery does not reveal how the first trap became script execution, or how the script turned into a proxy change or browser, or how a wallet address was changed before the target verified a transaction.
Two H1 investigations should be looked at in-depth. The first is a banking-malware campaign initiated with hacked corporate mailboxes and finished with browser manipulation and proxy.
In the second finding, a cryptocurrency campaign deployed a Rust-based clipper and got C2 infrastructure pointers from Binance Smart Chain.
The payloads are distinct, but none of the campaigns relied on breaking the genuine system at user end. The banking malware used a genuine account to set the trap whereas the clipper allowed the blockchain record an authentic transaction after modifying the local destination address.
The banking campaign attacked users in Lithuania, Poland, Slovakia, and Czechia. The lures appeared to be genuine business emails such as invoice messages, scanned document verifications, and shipment notices.
In various incidents, the texts were sent from hacked corporate mailboxes. The email was not designed to appear as if it came from an authentic organization. The emails were sent from an authentic account that threat actors had already hacked.
DKIM and SPF can still sail through when a message is sent via genuine infrastructure, whereas reputation systems may spot a sender with an authentic history.
The attachment deployed a JavaScript dropper, and then the chain travelled via PowerShell stages before reaching banking functionality and shellcode. The available signs indicate at GepyS.
The malware changed proxy settings and deployed a browser add-on, positioning itself nearby to the target’s banking session.
Demand for Cloudflare's cloud and security products has increased as more companies depend on its network to reliably route traffic and execute those technologies due to the rush to develop and expand AI agents.
For the first time, machines rather than people accounted for more than half of the traffic that passed throughout Cloudflare's (NYSE: NET) network last quarter.
Following Thursday's second-quarter results, the internet infrastructure company's shares surged to a record high on Friday morning, reaching over $325 before partially reversing the day's gains.
During the results call, CEO Matthew Prince stated, "In Q2, more than 50% of the traffic flowing across Cloudflare's network was not human for the first time in human history." Months before his own prediction, which had indicated the first part of 2027, the crossover occurred.
In light of this, Cloudflare increased its full-year revenue forecast to a range of $2.864 billion to $2.870 billion, or roughly 32% growth, and revenue increased 36% year over year to $696.1 million. Free cash flow increased 69% year over year to $56.4 million, while adjusted earnings per share came in at $0.29. Management directed revenue to increase by roughly 31% to $736 million to $737 million for the third quarter.
Additionally, there was a significant increase in customers. At the end of June, Cloudflare had 4,698 major customers, those that spend more than $100,000 annually, a 27% increase over the previous year. Additionally, current customers are spending more; dollar-based net retention, which measures how much the same customers spend after churn compared to a year ago, reached 120%, up 6 percentage points from a year ago and 2 percentage points from the first quarter.
Cloudflare is not yet paid by the machine traffic itself. Businesses who use the company's network for speed and cybersecurity pay subscriptions.
Therefore, handling a rapidly increasing amount of artificial intelligence (AI) crawler traffic primarily increases costs without increasing revenue. By that metric, Cloudflare becomes busier rather than larger in a majority-machine network.
Canada's federal banking regulator has privately warned financial institutions that advances in frontier artificial intelligence are shrinking the time available to detect and contain software vulnerabilities, according to an internal email that specifically identified Anthropic's Claude Mythos, an uncommon move for a regulator that typically avoids naming individual technologies.
The email, sent on April 29 by the Office of the Superintendent of Financial Institutions (OSFI), was addressed to chief technology officers, chief information security officers and chief risk officers at federally regulated banks and insurance companies. Obtained by Reuters through Canada's Access to Information Act, the communication described advanced AI models such as Anthropic's Claude Mythos as accelerating the pace at which cyber risks can emerge, prompting institutions to strengthen the speed of risk identification, mitigation and incident response.
Unlike most regulatory guidance, which generally refers to broad categories such as generative AI or emerging technologies, the OSFI email explicitly referenced Claude Mythos by name. Financial regulators typically adopt technology-neutral language to ensure guidance remains applicable as technologies evolve, making the direct reference to a specific frontier AI model particularly notable.
According to the released correspondence, OSFI warned that advanced AI systems are compressing the timeframe available for organizations to respond to newly identified vulnerabilities before they can be exploited. The regulator indicated that the bulletin accompanying the email outlined sound practices that federally regulated financial institutions could adopt to improve the speed and effectiveness of identifying, mitigating and responding to cyber risks.
However, portions of the document released under Canada's Access to Information Act were redacted, leaving many of the regulator's recommended practices undisclosed. While the details of the guidance remain partially withheld, the available sections reveal OSFI's assessment that rapidly advancing AI capabilities are challenging long-standing assumptions underpinning vulnerability management.
For decades, many cybersecurity programs have operated on the expectation that defenders would have days or even weeks to evaluate newly disclosed vulnerabilities, test patches and deploy mitigations before attackers developed reliable exploits. Frontier AI models capable of rapidly analyzing software code and identifying exploitable weaknesses could substantially reduce that window, increasing pressure on organizations to accelerate patch management and defensive operations.
The concern is particularly relevant for financial institutions, many of which continue to operate complex legacy infrastructure supporting critical banking services. Core banking platforms often consist of decades-old software integrated with newer digital systems, making security updates and vulnerability remediation significantly more complex than in less regulated technology environments. A shorter interval between vulnerability discovery and exploitation therefore presents operational challenges for institutions responsible for maintaining highly available financial services.
Claude Mythos has drawn attention within the cybersecurity community for its reported ability to assist with sophisticated vulnerability research and exploit development in controlled environments. Anthropic introduced the model through Project Glasswing, a restricted-access initiative designed to provide selected organizations with advanced cybersecurity capabilities for defensive research rather than broad public deployment. Access to the model remains limited and subject to eligibility requirements established by Anthropic.
The timing of OSFI's communication coincided with a series of regulatory discussions surrounding frontier AI models. Earlier in April, senior executives from Canadian banks reportedly met with regulators to discuss the implications of Claude Mythos. Around the same period, U.S. Treasury Secretary Scott Bessent and then-Federal Reserve Chair Jerome Powell also convened bank chief executives to examine the potential cybersecurity implications associated with increasingly capable AI systems.
International regulators have since demonstrated similar interest. Authorities at the European Central Bank and the Bank of England have reportedly discussed the implications of frontier AI for financial sector resilience, while Australia's corporate regulator, the Australian Securities and Investments Commission (ASIC), has confirmed that it is monitoring developments related to the technology.
Following questions from Reuters regarding the internal email, OSFI subsequently published a public bulletin addressing the governance of generative and agentic artificial intelligence. The regulator reiterated that its supervisory approach focuses on how federally regulated financial institutions identify, govern and manage risks arising from AI adoption rather than regulating individual AI models themselves.
"Our focus is not the technology itself, but how federally regulated financial institutions govern and manage the risks associated with its use," OSFI said in its public statement.
Nevertheless, the regulator's internal correspondence referred to Anthropic's Claude Mythos by name on multiple occasions, distinguishing it from the more general language typically used in regulatory communications concerning emerging technologies.
OSFI oversees Canada's federally regulated banks, insurance companies and pension plans, with responsibilities that include monitoring financial stability risks arising from cybersecurity, foreign interference, geopolitical developments and technological change. The emergence of highly capable AI models has increasingly placed these categories of risk in closer alignment as governments evaluate both the opportunities and security implications associated with frontier AI.
While the Canadian government has confirmed that it has access to Claude Mythos, it remains unclear whether any of Canada's major financial institutions currently participate in Anthropic's controlled-access Project Glasswing program. Several banks declined to comment publicly on whether they have access to the model, referring questions instead to the Canadian Bankers Association.
In response, the Canadian Bankers Association said member institutions have invested substantially in protecting Canada's financial system and continue to comply with OSFI's cybersecurity risk management and incident reporting requirements, without addressing whether banks currently have access to the frontier AI model.
At the same time, Canada's largest banks continue expanding their AI strategies across customer services, internal operations and software development. Royal Bank of Canada, TD Bank and Bank of Montreal have outlined initiatives aimed at integrating AI into business operations while reducing reliance on external technology vendors. Scotiabank, CIBC and National Bank have also disclosed AI-related programs intended to improve operational efficiency and customer services.
Bruce Ross, Royal Bank of Canada's Group Head of Artificial Intelligence, said in June that models such as Claude Mythos are changing the cyber threat environment by enabling exploit code to emerge much sooner after vulnerabilities are discovered. He said the bank's response has focused on strengthening AI-powered defensive capabilities to counter increasingly sophisticated attacks.
Anthropic has also expanded Project Glasswing in recent months, reporting that participating organizations have collectively identified more than 10,000 high- and critical-severity software vulnerabilities using the platform's advanced cybersecurity capabilities. The company has positioned the initiative as a defensive research program intended to improve software security while maintaining controlled access to highly capable AI systems.