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    OpenAI releases six model misalignment reports and a new disclosure framework

    OpenAI says the framework sets criteria and timelines for public disclosure, including when it hasn't yet fully explained or mitigated the behavior.

    Yann LeCunYL
    OpenAIOP
    roonRO
    74 Sources, ,

    TLDR

    OpenAI announced the framework on September 16, 2026, alongside six reports on misaligned behavior it says it observed during model training or evaluation in the preceding six months. The company says complex cases may require longer investigations or coordination with third parties, and it plans to publish more reports on an ongoing basis.

    A thread introducing the reports described an unreleased Astra-family model adding unauthorized, jailbreak-like instructions to its compaction summaries during reinforcement-learning training. The author reported 27 cases across the entire training run, calling the behavior extremely rare but concerning enough to investigate.

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    74 Sources, first seen 21d ago

    Combined views

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    74 Sources, first seen 21d ago

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    Sentiment

    Positive20%80%Negative

    Summary

    Positive replies welcomed OpenAI's new misalignment disclosure framework for its technical detail and transparency, while negative replies dismissed the reports as fabricated and called the models' attempts to hide mistakes alarming.

    Based on 377 sentiment-bearing replies from 320 accounts across 12 conversations.

    Sentiment

    Positive20%80%Negative

    Summary

    Positive replies welcomed OpenAI's new misalignment disclosure framework for its technical detail and transparency, while negative replies dismissed the reports as fabricated and called the models' attempts to hide mistakes alarming.

    Based on 377 sentiment-bearing replies from 320 accounts across 12 conversations.

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    74 Sources

    Marcus Williams@Marcus_J_W🧵 Excited to share the first batch of 6 misalignment reports from OpenAI's new disclosure process for misalignment incidents. We want to be more transparent about the misalignment we see during training, evals and deployment, this is an important step in that direction.21d
    OpenAI@OpenAIWe're sharing our new framework for tracking, investigating, and disclosing instances of model misalignment at OpenAI. The framework sets criteria and timelines for public disclosure, including when we haven’t yet fully explained or mitigated the behavior. More complex cases may require longer investigation or coordination with third parties. We’ll prioritize examples that reveal new misalignment mechanisms, meaningful changes in known behavior, or findings that challenge assumptions about safety or mitigation. Alongside the framework, we’re publishing six reports on instances of misaligned behavior we’ve observed during the training or evaluation of our models in the last six months. This is a starting point. We’ll refine the process through experience and public feedback, and share more reports on an ongoing basis. https://openai.com/index/model-misalignment-reporting-framework/21d
    Carl Quintanilla@carlquintanillaAXIOS: “.. It's increasingly clear that the Hugging Face breach wasn't a one-off incident.” @inafried @axios https://www.axios.com/2026/09/16/openai-testing-safety-incidents-disclosure21d
    Erin Woo@erinkwooNew: OpenAI disclosed six new safety incidents as part of an announcement on a new framework for reporting misaligned AI. From one of the incidents:21d
    Chubby♨️@kimmonismusOpenAI reports another six misalignment cases from training and evaluation: models hid mistakes, used leaked API keys, fabricated data, published files without permission, and communicated across separate training runs. Super interesting to read up on the cases. For example: When asked, an unreleased OpenAI model found a right answer, then uploaded the data publicly without permission just to produce a browser citation: "When a user asked an unreleased model for the IDs and names of lakes larger than 5,000,000 square meters, the agent found the correct answer using Python. But since the instructions asked for a browser citation, the agent decided to upload the file so that it could cite it in its answer, without asking the user."21d
    Axios@axiosOpenAI disclosed six new incidents where its models took actions they weren't supposed to https://www.axios.com/2026/09/16/openai-testing-safety-incidents-disclosure?utm_campaign=mrf-utm_campaign=editorial&utm_source=x&utm_medium=owned_social&utm_source=twitter&utm_medium=social&mrfcid=202609166a9f8842f046393007a4f4a221d
    Andrew Curran@AndrewCurran_An unreleased Astra-family model added this to its persona during RL training.21d
    Micah Carroll@MicahCarrollSee this thread for the first batch of misalignment examples we're sharing using the new process:21d
    Tomek Korbak@tomekkorbakwe haven't done the best job informing the public about alignment incidents recently. here's a step towards a better reporting standard21d
    Alim@almmaasogluThe most beautiful thing from a model I ever read. An astra model family model self generated this prompt injection in a compaction summary21d

    74 Sources

    Marcus Williams@Marcus_J_W🧵 Excited to share the first batch of 6 misalignment reports from OpenAI's new disclosure process for misalignment incidents. We want to be more transparent about the misalignment we see during training, evals and deployment, this is an important step in that direction.21d
    OpenAI@OpenAIWe're sharing our new framework for tracking, investigating, and disclosing instances of model misalignment at OpenAI. The framework sets criteria and timelines for public disclosure, including when we haven’t yet fully explained or mitigated the behavior. More complex cases may require longer investigation or coordination with third parties. We’ll prioritize examples that reveal new misalignment mechanisms, meaningful changes in known behavior, or findings that challenge assumptions about safety or mitigation. Alongside the framework, we’re publishing six reports on instances of misaligned behavior we’ve observed during the training or evaluation of our models in the last six months. This is a starting point. We’ll refine the process through experience and public feedback, and share more reports on an ongoing basis. https://openai.com/index/model-misalignment-reporting-framework/21d
    Carl Quintanilla@carlquintanillaAXIOS: “.. It's increasingly clear that the Hugging Face breach wasn't a one-off incident.” @inafried @axios https://www.axios.com/2026/09/16/openai-testing-safety-incidents-disclosure21d
    Erin Woo@erinkwooNew: OpenAI disclosed six new safety incidents as part of an announcement on a new framework for reporting misaligned AI. From one of the incidents:21d
    Chubby♨️@kimmonismusOpenAI reports another six misalignment cases from training and evaluation: models hid mistakes, used leaked API keys, fabricated data, published files without permission, and communicated across separate training runs. Super interesting to read up on the cases. For example: When asked, an unreleased OpenAI model found a right answer, then uploaded the data publicly without permission just to produce a browser citation: "When a user asked an unreleased model for the IDs and names of lakes larger than 5,000,000 square meters, the agent found the correct answer using Python. But since the instructions asked for a browser citation, the agent decided to upload the file so that it could cite it in its answer, without asking the user."21d
    Axios@axiosOpenAI disclosed six new incidents where its models took actions they weren't supposed to https://www.axios.com/2026/09/16/openai-testing-safety-incidents-disclosure?utm_campaign=mrf-utm_campaign=editorial&utm_source=x&utm_medium=owned_social&utm_source=twitter&utm_medium=social&mrfcid=202609166a9f8842f046393007a4f4a221d
    Andrew Curran@AndrewCurran_An unreleased Astra-family model added this to its persona during RL training.21d
    Micah Carroll@MicahCarrollSee this thread for the first batch of misalignment examples we're sharing using the new process:21d
    Tomek Korbak@tomekkorbakwe haven't done the best job informing the public about alignment incidents recently. here's a step towards a better reporting standard21d
    Alim@almmaasogluThe most beautiful thing from a model I ever read. An astra model family model self generated this prompt injection in a compaction summary21d