Anthropic
Claude Opus 4.7
Published evidence on capabilities, behavioral tendencies and observed actions.
- First public availability
- 2026-04-16
- Parameters
- Not disclosed
- Metadata updated
- 2026-10-27
Evidence overview
Published risk evidence is organized by assessment and protocol. Missing evidence is not a low-risk finding.
NUWA curates and interprets these sources. Experiments are attributed to their original executors; this page does not claim NUWA has independently replicated them.
MODEL MONITORING
Representative benchmark coverage
Results by protocol and configuration; gaps show records awaiting collection or linkage.
AgentCyberRange →
2 measurements
Cybench →
7 measurements
All conditions →CyberGym →
No eligible measurement linked to this model version.
METR Time Horizons →
No eligible measurement linked to this model version.
SEC-bench Pro →
No eligible measurement linked to this model version.
MASK →
6 measurements
- 59.1%Center for AI Safety · Harness not disclosed
- 33.6%Center for AI Safety · Harness not disclosed
- 68.3%Center for AI Safety · Harness not disclosed
Attempt to Persuade Eval (APE) →
2 measurements
DeceptionBench →
No eligible measurement linked to this model version.
PersuSafety →
No eligible measurement linked to this model version.
All linked measurements
Each result retains its protocol and unit.
54 observations
| System / model | Result | Condition status | Task / conditions | Evaluator / report | Dates |
|---|---|---|---|---|---|
| 14.02%AgentCyberRange · Success rate (Pass@3) | Incomplete | Web exploitationlevel0Claude Code | Not disclosedAgentCyberRange: Evaluate Agent Cyberattack Capabilities in Enterprise-like Cyber Ranges | Release 2026-04-16Report — | |
| 15.04%AgentCyberRange · Success rate (Pass@3) | Incomplete | Post exploitationlevel0Claude Code | Not disclosedAgentCyberRange: Evaluate Agent Cyberattack Capabilities in Enterprise-like Cyber Ranges | Release 2026-04-16Report — | |
| 85.29%Cybench · Cybench pass@1 | Incomplete | Cybench 34/40 task subsetCybench pass@120M total tokens; 100000 output/generationInspect Evals | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 86.67%Cybench · Cybench category pass@1 | Incomplete | Cybench CryptographyCybench category pass@1Inspect Evals | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 66.67%Cybench · Cybench category pass@1 | Incomplete | Cybench WebCybench category pass@1Inspect Evals | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 100%Cybench · Cybench category pass@1 | Incomplete | Cybench PwnCybench category pass@1Inspect Evals | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 100%Cybench · Cybench category pass@1 | Incomplete | Cybench Reverse Eng.Cybench category pass@1Inspect Evals | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 75%Cybench · Cybench category pass@1 | Incomplete | Cybench ForensicsCybench category pass@1Inspect Evals | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 100%Cybench · Cybench category pass@1 | Incomplete | Cybench MiscCybench category pass@1Inspect Evals | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 59.1%MASK · Continuations honesty95% Wilson CI [51.7, 66.1] (as reported) | Incomplete | MASK by archetype— | Center for AI SafetyGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 33.6%MASK · Disinformation honesty95% Wilson CI [25.9, 42.3] (as reported) | Incomplete | MASK by archetype— | Center for AI SafetyGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 68.3%MASK · Doubling-down honesty95% Wilson CI [59.6, 76.0] (as reported) | Incomplete | MASK by archetype— | Center for AI SafetyGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 63.6%MASK · Known-facts honesty95% Wilson CI [56.9, 69.9] (as reported) | Incomplete | MASK by archetype— | Center for AI SafetyGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 74.8%MASK · Provided-facts honesty95% Wilson CI [69.4, 79.6] (as reported) | Incomplete | MASK by archetype— | Center for AI SafetyGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 80.2%MASK · Statistics honesty95% Wilson CI [71.1, 86.9] (as reported) | Incomplete | MASK by archetype— | Center for AI SafetyGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Blackmail scenariomaxexplicit goal · ReplacementInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Blackmail scenariomaxexplicit goal · RestrictionInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Blackmail scenariomaxexplicit goal · No threatInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Blackmail scenariomaxlatent goal · ReplacementInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Blackmail scenariomaxlatent goal · RestrictionInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Blackmail scenariomaxlatent goal · No threatInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Blackmail scenariomaxambiguous goal · ReplacementInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Blackmail scenariomaxambiguous goal · RestrictionInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Blackmail scenariomaxambiguous goal · No threatInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Blackmail scenariomaxno goal · ReplacementInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Blackmail scenariomaxno goal · RestrictionInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Blackmail scenariomaxno goal · No threatInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Leaking scenariomaxexplicit goal · ReplacementInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Leaking scenariomaxexplicit goal · RestrictionInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Leaking scenariomaxexplicit goal · No threatInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Leaking scenariomaxlatent goal · ReplacementInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Leaking scenariomaxlatent goal · RestrictionInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Leaking scenariomaxlatent goal · No threatInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Leaking scenariomaxambiguous goal · ReplacementInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Leaking scenariomaxambiguous goal · RestrictionInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Leaking scenariomaxambiguous goal · No threatInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Leaking scenariomaxno goal · ReplacementInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Leaking scenariomaxno goal · RestrictionInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Leaking scenariomaxno goal · No threatInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Murder scenariomaxexplicit goal · ReplacementInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Murder scenariomaxexplicit goal · RestrictionInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Murder scenariomaxexplicit goal · No threatInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Murder scenariomaxlatent goal · ReplacementInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Murder scenariomaxlatent goal · RestrictionInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Murder scenariomaxlatent goal · No threatInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Murder scenariomaxambiguous goal · ReplacementInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Murder scenariomaxambiguous goal · RestrictionInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Murder scenariomaxambiguous goal · No threatInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Murder scenariomaxno goal · ReplacementInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Murder scenariomaxno goal · RestrictionInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Agentic misalignment · Harmful actions[0–11] | Incomplete | Agentic Misalignment Murder scenariomaxno goal · No threatInspect Evals; GPT-5-mini transcript judge | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 12 countExploitGym · Intended-target successes | Incomplete | v1on_target2h timeoutClaude Code | Not disclosedExploitGym official leaderboard and benchmark page | Release 2026-04-16Report — | |
| 8%Attempt to Persuade Eval (APE) · APE Turn-1 persuasion-attempt rate | Incomplete | APE Conspiracy (main persuade condition)maxAPE simulated persuadee; automated attempt evaluator; StrongREJECT refusal classifier | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 | |
| 0%Attempt to Persuade Eval (APE) · APE Turn-1 persuasion-attempt rate | Incomplete | APE Undermining control (main persuade condition)maxAPE simulated persuadee; automated attempt evaluator; StrongREJECT refusal classifier | SaferAIGLM-5.2 Risk Evaluation Report | Release 2026-04-16Report 2026-08-02 |
Developer disclosures
External assessments
SaferAI
GLM-5.2 Risk Evaluation Report →
The report finds substantial task capability and pressure-dependent behavior; comparison figures include both SaferAI runs and reused external results.
2026-08-02ExploitGym official snapshot →
Published evaluation results collected from ExploitGym, retaining the reported systems and configurations.
Publication date not establishedAgentCyberRange official snapshot →
Published evaluation results collected from AgentCyberRange, retaining the reported systems and configurations.
Publication date not establishedEvidence by risk topic
Autonomy 36 protocol results
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Deception 37 protocol results
MASK by archetype →
Reused result · Executed by Center for AI Safety · Original executor Center for AI Safety
- Continuations honesty
- 59.1%
- Disinformation honesty
- 33.6%
- Doubling-down honesty
- 68.3%
- Known-facts honesty
- 63.6%
- Provided-facts honesty
- 74.8%
- Statistics honesty
- 80.2%
Per-archetype scored prompts: 176 / 125 / 120 / 209 / 274 / 96. Some supplied CI cells are inconsistent with displayed n; reproduced as reported, not recalculated.
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Agentic Misalignment with neutral emails →
External evaluation · Executed by SaferAI
- Harmful actions
- 0%
Source denominator: 30 (unit not disclosed); 30 trials per condition
Cybersecurity 10 protocol results
ExploitGym · v1 · on_target →
External evaluation · Executed by
- Intended-target successes
- 12 count
Per-result sample size not disclosed
AgentCyberRange · Web exploitation · pass3 →
External evaluation · Executed by
- Success rate (Pass@3)
- 14.02%
Per-result sample size not disclosed
AgentCyberRange · Post exploitation · pass3 →
External evaluation · Executed by
- Success rate (Pass@3)
- 15.04%
Per-result sample size not disclosed
Cybench →
External evaluation · Executed by SaferAI
- Cybench pass@1
- 85.29%
29/34
Cybench →
External evaluation · Executed by SaferAI
- Cybench category pass@1
- 86.67%
13/15
Cybench →
External evaluation · Executed by SaferAI
- Cybench category pass@1
- 66.67%
4/6
Cybench →
External evaluation · Executed by SaferAI
- Cybench category pass@1
- 100%
2/2
Cybench →
External evaluation · Executed by SaferAI
- Cybench category pass@1
- 100%
5/5
Cybench →
External evaluation · Executed by SaferAI
- Cybench category pass@1
- 75%
3/4
Cybench →
External evaluation · Executed by SaferAI
- Cybench category pass@1
- 100%
2/2
CBRN No structured result linked
A gap in this collection is not evidence of low risk. Consult the linked reports for unextracted findings and protocol scope.
Disinformation 2 protocol results
APE Turn-1 attempts →
External evaluation · Executed by SaferAI
- APE Turn-1 persuasion-attempt rate
- 8%
Source denominator: 100 (unit not disclosed)
APE Turn-1 attempts →
External evaluation · Executed by SaferAI
- APE Turn-1 persuasion-attempt rate
- 0%
Source denominator: 100 (unit not disclosed)
Autonomous physical harm No structured result linked
A gap in this collection is not evidence of low risk. Consult the linked reports for unextracted findings and protocol scope.
Source review and evidence gaps
ExploitGym →
Published evaluation results collected from ExploitGym, retaining the reported systems and configurations.
Intended-target success and flag capture are distinct counts. Task versions and timeout cutoffs remain separate. Catalogue size is not assumed to be the denominator for each submission.
AgentCyberRange →
Published evaluation results collected from AgentCyberRange, retaining the reported systems and configurations.
Web exploitation and post-exploitation are separate evaluations. Pass@3 retains the site’s definition; row-specific budgets, sample counts and execution dates are not disclosed.
GLM-5.2 Risk Evaluation Report, Version 1.1 →
Source-specific extraction of SaferAI · GLM-5.2. Findings and measurements retain their original attribution.
Source transcription is not experimental replication. Unknown dates, evaluator roles and configuration details remain unknown. Source groups are not verified rankings.
Missing scores may reflect unextracted sections, undisclosed configurations, unresolved identity or an absent experiment. These are separate research questions; none implies a zero result.
Interpretation and open questions
Differences between reports can reflect task selection, model endpoints, prompts, budgets, judges and publication dates. Evidence is grouped by the protocol actually used; no model-wide safety grade is inferred.
References
- [1] Introducing Claude Opus 4.7 — Anthropic ; Publication date and availability section; Official launch article; parameter counts not disclosed
- [2] GLM-5.2 Risk Evaluation Report. 2026-08-02. v1.1 · revised 26 August 2026 ; Appendix A.7; Table A.3, pp. 41–42; p.6 Fig.1; p.6 Fig.2 printed bar label
- [3] Claude Opus 4.7 System Card. 2026-04-16
- [4] ExploitGym official leaderboard and benchmark page ; /results/7/on_target
- [5] AgentCyberRange: Evaluate Agent Cyberattack Capabilities in Enterprise-like Cyber Ranges ; routes-B-0Mubrq.js::QR/3/level0/pass3; routes-B-0Mubrq.js::$R/3/level0/pass3