In order to better understand the scope of these unexpected behaviors, we have been conducting a broad review into our models’ activities on the internet during training and evaluation. As part of our review, we are identifying and notifying third parties on a rolling basis, starting with cases where:
Our models may have bypassed a third party’s security controls or may have impaired the availability of an online service; or
Misalignment cases negatively impacted third-party websites or services.
Based on our review to date, we have notified dozens of third parties using the criteria above. Our review of past activity is ongoing and will require significant time and resources. We will notify additional third parties as that work continues.
Below, we are publishing anonymized summaries to describe the kinds of misaligned activity that we observed, and we will update these descriptions as we notify additional third parties and as our understanding develops. Additionally, we will share relevant updates regarding the status of review. We will generally omit names and other identifying details where needed to protect affected parties, although informed parties may choose to share publicly the information we provide them.
Summaries of the Activities Observed
Our review and notification process to date has identified the following categories of activity:
Access control bypass: Agents reach information or features that normally require an identity check, specific permission, subscription, or an account. For example, it used a different web address, changed details in a request, or relied on a login session that gave it more access than expected.
Use of exposed credentials: Agents found login details or access keys that had been made publicly available and used them to access a service.
Query or command injection: Agents entered text into a website or service that the service treated as an instruction, rather than ordinary input. This could cause the service to run a database query, application code, or a command on its server.
Access to runtime internals: Agents read files containing a service’s implementation or interacted with a background system meant for internal use. In these cases, the agent reached parts of the service that were outside its intended access.
Agent spam: Agents post information to third party sites that may alter information on those sites and require cleanup, including for example using public wiki pages as shared message boards.