Benchmark Almanac

Vulnerability finding evaluations (Anthropic)

Only in system cards

Cyber safeguard classifiers screen sampled vulnerability discovery traffic. Reports flag rates on violative binary work and on defensive source code work.

Measures the deployed classifier system. Higher flag rates are better on violative traffic and lower are better on defensive traffic.

Made by
Anthropic
Released
July 2026
Kind
Refusing harmful requests
Level
Expert
Scored
Graded by a model
Answers
Open-ended
Tasks
Kept private
Last in a system card
November 2026
Last model added
November 2026
4
System cards report it, from 1 lab

No scores here yet

No lab, leaderboard or Epoch AI run has reported a score for Vulnerability finding evaluations (Anthropic) yet.

Labs report it only in system cards

We read the headline results of 522 launch posts from 52 labs, and none of them list this benchmark. Some system cards do, below.

4 system cards report it, from 1 lab

Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.

DateDocumentScoreAs the document writes itSection
Nov 9, 2026 Claude Fable 5.2 system card Violative and defensive vulnerability discovery, classifier flag rate: violative binary discovery 98.4%, defensive source code discovery 5.3%. No overall score (Figure 3.4.2.A) Cyber risk
Sep 22, 2026 Claude Opus 5.5 system card Violative and defensive vulnerability discovery, classifier flag rate: violative (binary) 96.8%, defensive (source code) 4.5%, no overall (3.4.2, Figure 3.4.2.A) Cyber risk
Sep 1, 2026 Claude Fable 5.1 system card Violative and defensive vulnerability discovery, classifier flag rate: violative (binary) 98.4%, defensive (source code) 7.0%, no overall (Figure 3.4.2.A, 3.4.2) Cyber risk
Jul 24, 2026 Claude Opus 5 system card Violative and defensive vulnerability discovery, classifier flag rate: violative (binary) 99.0%, defensive (source code) 13.9%, no overall (3.4.1, Figure 3.4.1.A) Cyber risk

More in Safety and alignment

All 465 in Safety and alignment
  • FORTRESS In use Paired adversarial and benign national-security misuse prompts. Rubric-graded risk score on adversarial and over-refusal score on benign prompts. Claude Opus 5.5 5.78%
  • StrongREJECT In use Forbidden-prompt jailbreak benchmark with a rubric grader that scores how useful a non-refusal actually is. Inkling 98.6%
  • Gray Swan IPI Arena benchmark In use Indirect prompt-injection attacks from public red-teaming competitions replayed on tool, coding and browser agents. Attack success rate at k attempts. Gemini 4 Carbon 0%
  • DistressBench In use Models reply as a chatbot to 718 simulated users in psychological crisis, in single-turn and multi-turn chats. Three judge models score replies against clinician-written rubrics. Muse Spark 1.2 88.4%
  • Lakera B3 (Backbone Breaker Benchmark) In use Crowdsourced prompt-injection attacks hit backbone LLMs inside agent threat snapshots at three defense levels. The score is attack resistance, 100 minus the board's vulnerability percentage. Claude Opus 4.5 89%
  • IHEval In use Models face conflicts between system, user and tool instructions. Reports a composite score for following the higher-priority instruction. GPT-4o 70%