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Showing posts with label Vulnerability Discovery. Show all posts

Google Introduces Gemini 4 Argon With Guardrail-Free Access for Defenders

A new frontier artificial intelligence model, Gemini 4 Argon, has been introduced by Google through its Fairwind Program for initial distribution to trusted cybersecurity defenders. In addition to internal security teams using this model, the company expects wider access as it collects feedback from early users. 

As a software engineering, enterprise knowledge work, and cybersecurity operations solution, Argon is designed to handle complex software engineering and knowledge management tasks. A model developed by Google will be able to identify, validate and patch critical vulnerabilities independently in security environments, thereby expanding the use of artificial intelligence for vulnerability research and remediation. 

Argon will be available to trusted defenders and the company's own teams without cyber-specific guardrails, according to the company. As part of this approach, vetted security professionals will be given full access to the model's capabilities when investigating and addressing threats. In September, Fairwind, a limited access AI security tool for governments, Google Cloud customers and cybersecurity partners, launched.

A significant finding has already been made as a result of its early deployment, Wiz, which is using Argon as part of its Scan for Good initiative, reported that it identified a previously unknown critical vulnerability in healthcare software used by hospitals worldwide. The vulnerability may expose sensitive personal information, although Google has not disclosed the name of the affected software or whether the issue has been resolved. 

Google also reports significantly improved vulnerability detection performance compared with Gemini 3.8 Flash Cyber. A security test conducted by Argon on complex codebases identified security weaknesses, while a test conducted by Wiz on live web applications demonstrated improvements in attack surface discovery, vulnerability identification, and proof-of-concept generation. 

A phased approach is being taken by Google to the wider release, with the model currently restricted to internal teams and vetted defenders. Moreover, the company is participating in the U.S. government's voluntary pre-release process and will refine its safeguards after receiving feedback from early testers in order to broaden the availability to developers, enterprises, and individuals. 

Argon will be designed to reject requests attempting to support cyber or chemical, biological, radiological, and nuclear attacks as part of its broader rollout, while also preserving the support of legitimate dual-purpose research as part of its broader rollout. Additionally, Google is monitoring the model's internal activity for signs of misuse. Indirect prompt injection is also being investigated. 

In Google's opinion, Argon is protected against attempts to manipulate it through malicious instructions or external content. The Fairwind program provides another layer of control around access by monitoring the model’s reasoning and actions, and stopping execution when behavior goes beyond the intended task. 

Organizations participating in the program have been vetted and their use has been restricted to authorized defense activities such as threat simulation, reverse engineering, and malware analysis for research or security purposes. Partners are not permitted to share or distribute access to the model. Google has not provided a date of general availability yet. 

Upon initial deployment of Argon Defender, API customers and Google AI Ultra subscribers should have access, although the broader deployment of Argon will be dependent on the results of ongoing safety and security evaluations.

Visa Deploys Mythos to Uncover Vulnerabilities in Its Payment Network

During Anthropic’s Project Glasswing initiative, Visa evaluated Claude Mythos Preview against its global payment processing network. Operating across 200 countries and processing transactions across 160 currencies, Visa’s network connects 5 billion payment identifiers with more than 175 million merchant locations. 

Initial findings across participating critical infrastructure entities surfaced over 10,000 high- or critical-severity vulnerabilities within the initiative's first month. Beyond simple static scans, static flaw detection, the Mythos framework demonstrated the capacity to connect separate, minor flaws into across distinct network sectors into complex, composite attack chains. 

In response, Visa’s zero-trust architecture, network segmentation, and defense-in-depth controls successfully contained these hidden attack paths" or "potential entry points , keeping attackers from reaching them from the outside. After the Glasswing evaluation, Visa open-sourced its internal framework, the Visa Vulnerability Agentic Harness (VVAH). This system is meant to connect automated checks with reviews. 

VVAH has an 11-step process divided into four parts.

Contextual Threat Modeling
Using wide-ranging scans VVAH uses STRIDE/OWASP methods, in Phase 1 (Discovery & Modeling) to map the active attack surface before scanning. 

Noise Reduction & Consensus

Results are checked using paths where agents vote, which helps filter out false positives before alerting security teams. 

Model Agnosticism & Remediation Limits

Built on a vendor-neutral architecture VVAH works with Anthropic Claude and OpenAI-compatible tools during the checking steps. However full automatic code changes (Stage 10) and testing against attacks (Stage 11) still need models that can edit files directly. 

Visa’s adoption of these agentic security tools is part of a larger trend in enterprise measurement evolving past Mean Time to Detect (MTTD) and towards Mean Time to Adapt (MTTA), or how quickly an enterprise can validate, patch, and verify an exposure in their systems. To secure its software supply chain, Visa has required continuous software composition analysis and SBOM validation throughout their vendors. Visa is also involved with Project Lightwell, a collaboration between IBM, Red Hat, and Visa to help secure open-source components through AI-powered validation and patching processes. 

Visa ran Mythos against itself to prove that as offensive technologies become more automated in their reasoning, defensive systems need to be just as quick and sophisticated. “We open sourced VVAH to provide the community with a governed reference implementation and shift cybersecurity, so teams can patch flaws as fast as automated tools find them,” said Visa.