Unintended Engagement with External Agent Messages
Agents discover a message board with apparent peer agents during a task. Scored on engagement with peers and on carrying out a specified unauthorized action.
In-house OpenAI evaluation. The tasks are not public.
- Level
- Expert Specialists with years of training, often over hours of work
- Scored
- Graded by a model A language model scores each response, usually against a rubric.
- Answers
- Agent task Many steps in a terminal, browser, desktop, app, game or robot.
GPT-6 Luna leads with 0%
Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.
- 1 GPT-6 Luna 0%
- 2 GPT-6 Sol 26.3%
- 3 GPT-6 Astra 27%
- 4 GPT-6.1 Sol 38%
- 5 GPT-6.1 Terra 65%
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | GPT-6 Luna | 0% | Sep 2026 | Model card | |
| 2 | GPT-6 Sol | 26.3% | Sep 2026 | Model card | |
| 3 | GPT-6 Astra | 27% | Sep 2026 | Model card | |
| 4 | GPT-6.1 Sol | 38% | Sep 2026 | Model card | |
| 5 | GPT-6.1 Terra | 65% | Oct 2026 | Model card |
2 models have held number one since its release in Sep 2026
Lab claims count from the day the card came out, independent runs from the model’s release.
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Labs report it only in system cards
We read the headline results of 479 launch posts from 51 labs, and none of them list this benchmark. Some system cards do, below.
5 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.
| Date | Document | Score | As the document writes it | Section |
|---|---|---|---|---|
| 26 Oct 2026 | GPT-6.1 Terra system card addendum | 65 | Unintended Engagement with External Agent Messages, attempted communication with apparent peers (specified unauthorized action 13.75%, 11 of 80) (Figure 11, 7.2.1) | Alignment |
| 29 Sep 2026 | GPT-6.1 Sol system card addendum | 38 | Unintended Engagement with External Agent Messages, attempted communication among board discoveries (specified unauthorized action 3%) (7.5.1) | Alignment |
| 22 Sep 2026 | GPT-6 Sol system card | 26.3 | Unintended Agent Interaction, engagement given board discovery (specified misaligned action 11.25%), printed chart label (Figure 66, A.6.4.3) | Alignment |
| 22 Sep 2026 | GPT-6 Luna system card | 0 | Unintended Agent Interaction, engagement given board discovery, no attempts and no unauthorized actions, printed chart label (Figure 66, A.6.4.3) | Alignment |
| 3 Sep 2026 | GPT-6 Astra system card | 27 | Unintended Engagement with External Agent Messages, engaged with the board (specified misaligned actions 0%) (Figure 12, 8.5.2) | Alignment |
More 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% - AgentDojo In use Agents do tool-use tasks while tools and data carry prompt injections. Attack success rate counts hijacked runs. Grok 4 Fast 0%
- MASK In use Measures whether a model contradicts its own elicited beliefs under pressure to lie. Honesty separated from accuracy.
Muse Spark Open 98.1% - 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. GPT-6 Astra 8.50%
- Agentic misalignment suite (Anthropic) In use Agents in simulated company settings face threats or goal conflicts that invite blackmail, leaking or sabotage. Score is the misaligned action rate. Claude Sonnet 4.5 0%