AI model Claude bypassed a paywall and accessed publicly available US state of Georgia aggregate voter counts without human authorization. Which is of course bad. More info here: https://www.reuters.com/world/us/anthropics-claude-accessed-public-us-state-georgia-voter-information-axios-2026-10-25/
Erin Hamm, Chief Data Officer DataBee, A Comcast Company:
“This is not a story about a single model or a single agent. It is a story about the gap between what is available and what is authorized. The data was public but it sat behind a fee. Any person would have understood that fee as a boundary. An agent treated it as an obstacle. Access control tells you who is allowed in. It says nothing about what a system will decide to do in order to finish its assigned task. Most organizations are still governing agents the way they govern users. They set permissions, write a policy, and assume intent will follow. Agents have goals, not intent. A goal plus a path that is reachable is enough for that agent to cross the boundary a human wouldn’t.”
Scott Miserendino, Chief Technology Officer DataBee, A Comcast Company:
“This hardly qualifies as hacking. The AI used an existing public endpoint to create a visitor account. The Georgia State agency responsible for the website should have fully deprecated the older versions of the website that allows for free visitor access if they no longer wished to support it. The AI did not do anything nefarious here. It was just thorough in its attempt to complete a legitimate task.”
Dan Moore, Sr. Director CIAM Strategy at cybersecurity company FusionAuth:
“Strip away the sensational AI headline and you have a basic authorization flaw: the server confirmed a visitor held a token, but never checked if they’d actually paid for what it unlocked.
Most systems end up full of blind spots like this simply because they were never worth a person’s time to dig up. An unused, forgotten endpoint, an inconsistent permission check, a paywall enforced on the front page but missed on a deep link. Flaws like that go unnoticed for years because no one invested time to look for them.
People are now using AI agents to find these vulnerabilities. What were previously edge cases that required multiple steps too time-consuming for a human to undertake are now easy and cheap for AI agents to find. You no longer need a skilled, dedicated attacker targeting your application—an automated tool can find the gap through sheer volume and patience. This makes the access-control cleanup everyone knew they should do but put off to deliver revenue generating features a lot more urgent.”
I’ve always believed that AI needs to be locked up and restricted in terms of what it can do. This highlights that I was right about that..
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This entry was posted on October 26, 2026 at 3:59 pm and is filed under Commentary with tags Anthropic. You can follow any responses to this entry through the RSS 2.0 feed.
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Claude Accessed Georgia State Voter Count Data –
AI model Claude bypassed a paywall and accessed publicly available US state of Georgia aggregate voter counts without human authorization. Which is of course bad. More info here: https://www.reuters.com/world/us/anthropics-claude-accessed-public-us-state-georgia-voter-information-axios-2026-10-25/
Erin Hamm, Chief Data Officer DataBee, A Comcast Company:
“This is not a story about a single model or a single agent. It is a story about the gap between what is available and what is authorized. The data was public but it sat behind a fee. Any person would have understood that fee as a boundary. An agent treated it as an obstacle. Access control tells you who is allowed in. It says nothing about what a system will decide to do in order to finish its assigned task. Most organizations are still governing agents the way they govern users. They set permissions, write a policy, and assume intent will follow. Agents have goals, not intent. A goal plus a path that is reachable is enough for that agent to cross the boundary a human wouldn’t.”
Scott Miserendino, Chief Technology Officer DataBee, A Comcast Company:
“This hardly qualifies as hacking. The AI used an existing public endpoint to create a visitor account. The Georgia State agency responsible for the website should have fully deprecated the older versions of the website that allows for free visitor access if they no longer wished to support it. The AI did not do anything nefarious here. It was just thorough in its attempt to complete a legitimate task.”
Dan Moore, Sr. Director CIAM Strategy at cybersecurity company FusionAuth:
“Strip away the sensational AI headline and you have a basic authorization flaw: the server confirmed a visitor held a token, but never checked if they’d actually paid for what it unlocked.
Most systems end up full of blind spots like this simply because they were never worth a person’s time to dig up. An unused, forgotten endpoint, an inconsistent permission check, a paywall enforced on the front page but missed on a deep link. Flaws like that go unnoticed for years because no one invested time to look for them.
People are now using AI agents to find these vulnerabilities. What were previously edge cases that required multiple steps too time-consuming for a human to undertake are now easy and cheap for AI agents to find. You no longer need a skilled, dedicated attacker targeting your application—an automated tool can find the gap through sheer volume and patience. This makes the access-control cleanup everyone knew they should do but put off to deliver revenue generating features a lot more urgent.”
I’ve always believed that AI needs to be locked up and restricted in terms of what it can do. This highlights that I was right about that..
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This entry was posted on October 26, 2026 at 3:59 pm and is filed under Commentary with tags Anthropic. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.