Claude Opus 4.6 Generated Chrome Exploit for $2,283 in API Costs
Anthropic's Claude Opus 4.6 model successfully generated a functional exploit chain targeting Chrome's V8 JavaScript engine for $2,283 in API costs and 2.3 billion tokens. Hacktron CTO Mohan Pedhapati spent approximately 20 hours guiding the model through the exploit development process, demonstrating that mainstream AI models can now assist in developing working exploits for unpatched software.
Claude Opus 4.6 Generated Chrome Exploit for $2,283 in API Costs
Anthropic's Claude Opus 4.6 model successfully generated a functional exploit chain targeting Chrome's V8 JavaScript engine for $2,283 in API costs, according to research published by Hacktron CTO Mohan Pedhapati.
The demonstration, which cost 2.3 billion tokens and required approximately 20 hours of human guidance, targeted Chrome 138 bundled in Discord. The exploit chain successfully achieved code execution—demonstrated by opening the calculator app, a standard proof-of-concept indicator.
Cost Analysis and Implications
At $2,283, the exploit development cost represents a fraction of what comparable manual work would require. Pedhapati notes this amount is significantly less than the theoretical $15,000 reward available through Google's and Discord's vulnerability reward programs, even before accounting for the weeks of manual work saved.
The research used publicly known vulnerabilities from Chrome 146—the same version running in Anthropic's own Claude Desktop application—to demonstrate the exploit development capabilities.
Model Capabilities and Safeguards
According to Anthropic's Opus 4.7 System Card, the newer Opus 4.7 model released Thursday shows "roughly similar" cyber capabilities to Opus 4.6. However, Opus 4.7 includes safeguards that "automatically detect and block requests that indicate prohibited or high-risk cybersecurity uses."
Anthropic has withheld its Mythos bug-finding model from public release specifically due to concerns about enabling attackers to find and exploit vulnerabilities before patches are available. Despite this, Pedhapati's work demonstrates that publicly available models already possess significant exploit development capabilities.
Security Implications
The research highlights a critical security challenge: Discord was running Chrome 138, nine major versions behind the current Chrome 147.0.7727.101/102. Electron 41.2.1, released April 15, bundles Chrome 146.0.7680.188—just one version behind current—but Electron-based applications don't necessarily update their dependencies immediately.
"Whether Mythos is overhyped or not doesn't matter," Pedhapati said. "The curve isn't flattening. If not Mythos, then the next version, or the one after that. Eventually, any script kiddie with enough patience and an API key will be able to pop shells on unpatched software."
Recommendations
Pedhapati argues that as AI models become more capable of exploit development, the vulnerability window narrows significantly. His recommendations include:
- Implementing automatic security patches to eliminate user dependency on manual updates
- Focusing on security before code deployment
- Faster dependency updates, particularly for Electron-based applications
- More cautious disclosure timing for open source projects, as "every public commit is a starting gun for anyone with an API key"
What This Means
This demonstration confirms that publicly available frontier AI models have reached the capability threshold for practical exploit development, even if they require human guidance to overcome obstacles. The $2,283 price point makes this accessible to a wide range of actors, not just nation-states or well-funded groups. The security industry's traditional patch-and-update cycle may be insufficient when AI can accelerate exploit development from weeks to days. Organizations running software with known vulnerabilities—particularly Electron-based applications lagging behind Chrome releases—face materially increased risk.
Related Articles
Anthropic Opens Cyber Verification Program to More Security Teams With Reduced Claude Safety Filters
Anthropic is expanding its Cyber Verification Program (CVP) to a much larger pool of vetted security professionals, giving them access to Claude's most powerful models with reduced safety filters. Access is split into three tiers: Defense, Red Team, and Specialized. Anthropic claims partners in its predecessor program, Project Glasswing, found at least 129,000 confirmed vulnerabilities between April and July 2026.
Anthropic Python SDK v1.15.0 adds speed parameter to Messages API and usage.speed field
Anthropic released v1.15.0 of its Python SDK, adding a `speed` parameter and `usage.speed` field to the Messages API. The release also adds a `between_tools` thinking type to model capabilities and exposes a Console organization's usage-tier spend cap as a read-only spend limit.
Google and Meta unveil frontier models they claim match OpenAI and Anthropic's best
Google and Meta each unveiled a new frontier model within a span of days, and both companies claim the models can compete with the best from OpenAI and Anthropic. Independent benchmarks, pricing and technical specifications were not available in the source reporting.
Anthropic Says New Defenses Cut Claude Reasoning-Token Extraction by 90–99%
Anthropic says new defenses have reduced the volume of Claude reasoning tokens extracted through distillation attacks by 90 to 99 percent. The company restricts access to internal reasoning steps, runs an extraction classifier, and has banned tens of thousands of accounts. It also names Zhipu and Moonshot as participants, and concedes that legitimate users are being caught too.
Comments
Loading...