Unverified50% confidenceFactExact time
Among the vulnerabilities GTIG could identify as possibly AI-discovered, low-risk findings dropped to 39% (69% for traditional findings), medium-risk rose to 58% (28% for traditional), and exactly 50% of AI-discovered vulnerabilities led to remote code execution, versus 26% across the entire ecosystem.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/16/2026
First Seen
Valid until: 1/14/2027
Sources
Related Entities
Related Claims
UnverifiedOver the past six months, Anthropic used its model to identify more than 29,000 suspected vulnerabilities in open-source code, but only approximately 6,000 have been manually reviewed; of 97 high-severity findings across 48 reviewed projects, 88% met the standard, with the true positive rate expected to exceed 90%.76% similarUnverifiedIn the control test, relying solely on prompts to instruct the AI to write less code saved about 30% of lines, but security dropped to 95%.69% similarUnverifiedThe more detailed the answers provided to the AI during the requirements analysis phase, the lower the probability of bugs in the final product; the cost of fixing errors found in the requirements phase is only 1/10 to 1/100 of the cost of finding the same type of error in the coding phase.68% similarUnverifiedadversa.ai's CodePoisonRAG research planted 85 poisoned samples across three code-generation agents, achieving attack success rates of 0.80 to 0.93.67% similarUnverifiedGemini 4 Argon's failure rate on code audit benchmarks ranges between 50% and 70%, with all three independent projects showing high false-positive rates.66% similar
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