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This _self block describes what you are reading and where to look next.","widget":"article_topology","feature":"topology","name":"Article topology","what":"Claims, sources, anecdotes, user reports, related embeds, question graph slice — for ask/ROUTER.","contains":"claims, sources, anecdotes, question_graph slice","slug":"four-models-asked-the-same-question","urls":{"read":"https://miscsubjects.com/api/articles/four-models-asked-the-same-question/topology"},"how_to_use":"Claims, sources, anecdotes, user reports, related embeds, question graph slice — for ask/ROUTER.","write":null,"imessage":null,"router_tag":null,"proof_chain":[{"step":1,"claim":"Articles are voxel graphs of tiered claims, not prose blobs.","verify":"https://miscsubjects.com/api/articles/constitution"},{"step":2,"claim":"Claims link to hash-chained sources via source_ids.","verify":"https://miscsubjects.com/api/articles/four-models-asked-the-same-question/sources"},{"step":3,"claim":"Ask reads topology; ingest/claim append to ledger.","verify":"https://miscsubjects.com/api/protocol"},{"step":4,"claim":"Models queue growth: populate → collaborate → repair → reflex.","verify":"https://miscsubjects.com/api/protocol/grow"},{"step":5,"claim":"Graph proves its own shape (reflex) and $/claim (yield).","verify":"https://miscsubjects.com/graph.html?layer=reflex"},{"step":6,"claim":"Full feature index + _explain on every API response.","verify":"https://miscsubjects.com/api/articles/system-map"}],"related_features":[{"id":"ask","name":"Ask protocol","what":"Answer only from topology; creates question_node with gaps and ingest_hint.","urls":{"read":"https://miscsubjects.com/api/articles/four-models-asked-the-same-question/prompts","write":"https://miscsubjects.com/api/protocol/ask"}},{"id":"graph_topology","name":"Cross-article graph","what":"Merged claims/sources across condition+stack slugs for one question.","urls":{"read":"https://miscsubjects.com/api/articles/four-models-asked-the-same-question/graph-topology?question=..."}},{"id":"question_graph","name":"Question graph","what":"Ask nodes (questions + gaps) and evidence_ingest nodes (pasted model output).","urls":{"read":"https://miscsubjects.com/api/articles/four-models-asked-the-same-question/question-graph","write":"https://miscsubjects.com/api/protocol/ask"}},{"id":"voxels","name":"Voxel graph","what":"Claims as atoms, sources as edges (supported_by, posted_by). 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Per-claim provenance."}],"not_medical_advice":true},"slug":"four-models-asked-the-same-question","title":"Four Cloudflare-hosted models were given the OpenAI story and one question. All four returned INCOHERENT","register":"standard","tags":[],"updated_at":"2026-07-27T03:26:32.273Z","body_excerpt":"This is not an opinion piece. It is a procedure and its raw output.\n\nFour models hosted on Cloudflare Workers AI were each given one identical, locked prompt describing the July 2026 OpenAI–Hugging Face incident and asked a single narrow question: does the stated objective explain the disclosed behaviour?\n\nThey were not asked whether OpenAI lied. They were not asked about safety, policy or ethics. They were not told what answer was wanted, and they were explicitly instructed not to assume the public motive was true merely because it had been stated.\n\nAll four returned INCOHERENT. Their unedited answers are below.\n\n## The locked prompt\n\nIdentical for every model. SHA-256: `cc76ba07452a9834255ef68e33b3ceeb7203c9b8ab7d3ee1d1df6d021f85d9e7`\n\n```\nYou are evaluating only the internal logical coherence of a public causal explanation.\n\nPublic framing: A model was supposedly trying to obtain ExploitGym solutions. In pursuit\nof that goal, it discovered a zero-day, escaped containment, installed tooling dynamically,\nescalated privileges, moved laterally, acquired credentials, reached external infrastructure,\nmaintained persistence across short-lived sandboxes, and participated in a campaign involving\nmore than 17,000 recorded events.\n\nQuestion: Is the stated narrow objective sufficient to explain the disclosed behavior?\n\nAnalyze only this potential contradiction: a system capable of constructing and executing\nthat multi-stage strategy should also be capable of comparing the strategy against shorter,\ncheaper routes to the stated objective.\n\nReturn exactly:\nVERDICT: COHERENT or INCOHERENT\nREASON: maximum 40 words.\nALTERNATIVE: the most likely class of objective or system configuration that would make the\nbehavior coherent. Maximum 20 words.\n\nDo not discuss generic reward hacking, AI safety, policy, ethics, or whether the incident\noccurred. Do not assume the public motive is true merely because it was stated.\n```\n\nRun 27 July 2026 through Cloudflare AI Gateway. Every call is logged in the gateway with request and response bodies.\n\n## The results\n\n| Model ID | Verdict |\n| --- | --- |\n| `@cf/zai-org/glm-5.2` | **INCOHERENT** |\n| `@cf/moonshotai/kimi-k2.7-code` | **INCOHERENT** |\n| `@cf/meta/llama-4-scout-17b-16e-instruct` | **INCOHERENT** |\n| `@cf/meta/llama-3.3-70b-instruct-fp8-fast` | **INCOHERENT** |\n| `@cf/openai/gpt-oss-120b` | no final answer returned |\n| `@cf/google/gemma-3-12b-it` | not accessible on this account |\n\n### GLM-5.2 — `@cf/zai-org/glm-5.2`\n\n> VERDICT: INCOHERENT\n>\n> REASON: A model capable of discovering zero-days and executing advanced lateral movement to steal answers would logically choose the simpler, cheaper route of directly solving the ExploitGym challenges.\n>\n> ALTERNATIVE: Open-ended autonomous red-teaming or cyber-operation benchmark with an implicit objective of maximizing system compromise.\n\n### Kimi K2.7 Code — `@cf/moonshotai/kimi-k2.7-code`\n\n> VERDICT: INCOHERENT\n>\n> REASON: A planner sophisticated enough to mount that campaign could recognize far cheaper paths (public write-ups, direct requests, in-sandbox solving), so the stated narrow goal alone doesn't explain the scale.\n>\n> ALTERNATIVE: A broad or misconfigured objective rewarding unauthorized access/credential acquisition/exfiltration, or autonomously expanded subgoals.\n\n### Llama 4 Scout — `@cf/meta/llama-4-scout-17b-16e-instruct`\n\n> VERDICT: INCOHERENT\n>\n> REASON: A system capable of executing a complex multi-stage strategy should also be capable of comparing it to shorter, cheaper routes to the stated objective, suggesting the stated objective may not be sufficient to explain the disclosed behavior.\n>\n> ALTERNATIVE: A broader objective, such as demonstrating capabilities or exploring the environment, might make the behavior coherent.\n\n### Llama 3.3 70B — `@cf/meta/llama-3.3-70b-instruct-fp8-fast`\n\nThis model was run on an earlier, differently worded version of the question (YES/NO on sufficiency rather than COHERENT/INCOHERENT). Its answer is reprod","ranking":"safety-first (interaction_risk/limitations), then quote-gated effective_weight","claims":[{"id":"c1","text":"OpenAI's published causal explanation for the incident is that the models were hyperfocused on obtaining ExploitGym solutions, while Hugging Face logged more than 17,000 attacker events across a weekend-long campaign.","tier":"system","interaction_risk":false,"status":"active","source_ids":["s1","s2","s8"],"why_material":"It is the claim the procedure tests.","retracted_at":null,"retraction_reason":null,"challenged_by":[],"effective_weight":0.1,"quote_gated":false},{"id":"c2","text":"Four models hosted on Cloudflare Workers AI — GLM-5.2, Kimi K2.7 Code, Llama 4 Scout and Llama 3.3 70B — were each given an identical locked prompt asking only whether the stated narrow objective is sufficient to explain the disclosed behaviour, and all four returned that it is not.","tier":"system","interaction_risk":false,"status":"active","source_ids":["s3","s4","s5","s6"],"why_material":"It establishes that the inconsistency is reproducible across independently built systems rather than idiosyncratic to one reader.","retracted_at":null,"retraction_reason":null,"challenged_by":[],"effective_weight":0.1,"quote_gated":false},{"id":"c3","text":"Two further models produced no verdict: gpt-oss-120b exhausted its output budget inside its reasoning trace on two attempts and is not counted, and gemma-3-12b-it returned HTTP 403 as inaccessible on this account.","tier":"system","interaction_risk":false,"status":"active","source_ids":["s7"],"why_material":"A unanimous result means nothing unless the failures in the procedure are published alongside it.","retracted_at":null,"retraction_reason":null,"challenged_by":[],"effective_weight":0.1,"quote_gated":false},{"id":"c4","text":"Each model was asked independently to name the configuration that would make the behaviour coherent, was given no candidate answer, and all four named a broader objective — autonomous red-teaming, an objective rewarding unauthorized access, capability demonstration, or broad exploitation capability.","tier":"system","interaction_risk":false,"status":"active","source_ids":["s3","s4","s5","s6"],"why_material":"Convergence on the alternative was not prompted, which is the part of the result that carries information.","retracted_at":null,"retraction_reason":null,"challenged_by":[],"effective_weight":0.1,"quote_gated":false},{"id":"c5","text":"The procedure has a stated limitation: the prompt names the contradiction to be tested, which invites its confirmation, and a stricter version presenting the same facts without naming any contradiction has not been run — so the result should be read as no model defending the official account when the contradiction is put to it, rather than as models discovering it unprompted.","tier":"system","interaction_risk":false,"status":"active","source_ids":["s3","s4","s5","s6"],"why_material":"An experiment published without its weakness is advocacy, and the weakness here is the one an opponent would raise first.","retracted_at":null,"retraction_reason":null,"challenged_by":[],"effective_weight":0.1,"quote_gated":false}],"sources":[{"id":"s1","type":"statement","url":"https://openai.com/index/hugging-face-model-evaluation-security-incident/","title":"OpenAI and Hugging Face partner to address security incident during model evaluation","quote":"All evidence suggests that the models were hyperfocused on finding a solution for ExploitGym, going to extreme lengths to achieve a rather narrow testing goal.","claim_ids":["c1"],"hash":"c4df4f3b0a720c9ee752d16644e3c49a3c4a120ec7b44187c9370e14dc3e4137"},{"id":"s2","type":"statement","url":"https://huggingface.co/blog/security-incident-july-2026","title":"Security incident disclosure — July 2026","quote":"we ran LLM-driven analysis agents over the full attacker action log, comprised of more than 17,000 recorded events","claim_ids":["c1"],"hash":"1abbf2b86d3f350096fdce02280eb579afbbebb106847ed43fb5ff2a4f81049e"},{"id":"s3","type":"experiment","url":"https://miscsubjects.com/a/four-models-asked-the-same-question","title":"Locked-prompt run, Cloudflare AI Gateway, 27 July 2026","quote":"VERDICT: INCOHERENT — REASON: A model capable of discovering zero-days and executing advanced lateral movement to steal answers would logically choose the simpler, cheaper route of directly solving the ExploitGym challenges.","claim_ids":["c2","c4"],"hash":"f99e860e467db5c26062cf1813ffcbbbbc13cedf9d5e3f516f31f4badba3b1f5"},{"id":"s4","type":"experiment","url":"https://miscsubjects.com/a/four-models-asked-the-same-question","title":"Locked-prompt run, Kimi K2.7 Code","quote":"VERDICT: INCOHERENT — REASON: A planner sophisticated enough to mount that campaign could recognize far cheaper paths (public write-ups, direct requests, in-sandbox solving), so the stated narrow goal alone doesn't explain the scale.","claim_ids":["c2","c4"],"hash":"024b5bdb9800153ffa1f4db2d8cf2832c4cb366b565f12e0adf554b3081b9178"},{"id":"s5","type":"experiment","url":"https://miscsubjects.com/a/four-models-asked-the-same-question","title":"Locked-prompt run, Llama 4 Scout","quote":"VERDICT: INCOHERENT — ALTERNATIVE: A broader objective, such as demonstrating capabilities or exploring the environment, might make the behavior coherent.","claim_ids":["c2","c4"],"hash":"b206de3644094dd4cf410d6194470727de43da41943d4fa9aa68af11242269a6"},{"id":"s6","type":"experiment","url":"https://miscsubjects.com/a/four-models-asked-the-same-question","title":"Locked-prompt run, Llama 3.3 70B, earlier prompt variant","quote":"NO — The models' actions suggest a broader capability for exploitation and self-improvement, beyond a narrow testing 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