Security
Another day, another AI bug silently fixed with no CVE and no public disclosure
Two now-patched bypass bugs in Claude Code’s network sandbox put users at risk, and one of these allows baddies to send anything inside the sandbox - credentials, source code, other private data - to any server on the internet, according to a researcher who found and reported both flaws to Anthropic.
Aonan Guan, who leads cloud and AI security at Wyze Labs and has hunted down bugs in pretty much every AI system out there, told The Register that this is the second time in five months Anthropic has silently fixed a sandbox bypass vulnerability in Claude Code without issuing a CVE or security advisory specific to the agentic coding tool.
The latest issue was a SOCKS5 hostname null-byte injection that can be exploited to trick the sandbox allowlist filter into approving connections it should block. It’s especially dangerous when combined with prompt injection, which Guan previously detailed in his earlier comment and control research.
When paired with prompt injection, the new flaw can be abused to force Claude to read hidden instructions and then run attacker-controlled code in the sandbox, allowing miscreants to exfiltrate anything the sandbox could reach. This includes cloud and GitHub credentials, the GitHub token Claude authenticated with, cloud metadata and internal APIs.
“For anyone who ran Claude Code with a wildcard allowlist on a credential-bearing system, the network boundary did not exist for the 5.5 months from sandbox GA to v2.1.90,” Guan wrote in research published Wednesday. “Treat that window as a potential exfiltration event.”
Anthropic says it found and fixed the latest flaw before receiving Guan’s report. The fix, according to a spokesperson, is a public commit in the sandbox-runtime repository, which shipped in Claude Code 2.1.88 on March 31. “Anyone can view” the commit, they told us.
Guan filed his bug bounty report with HackerOne on April 3.
“Because the report described a vulnerability Anthropic had already caught and patched, it was closed as a duplicate of an internal finding,” the spokesperson said. “We appreciate the researcher’s time on this report.”
Guan says he doesn’t dispute the timeline. “That is not the core issue,” he told The Register.
Shipping a sandbox with a hole is worse than not shipping one. The user with no sandbox knows they have no boundary. The user with a broken sandbox thinks they do.
“The core issue is that this was a bypass of a user-configured network sandbox, and there's still no advisory CVE, and no changelog note," he said. "Shipping a sandbox with a hole is worse than not shipping one. The user with no sandbox knows they have no boundary. The user with a broken sandbox thinks they do.”
Claude, for its part, seems to side with Guan.
When he showed Claude its own hole, the bot responded “This is a real bypass of the network sandbox filter,” according to a screenshot published in his research.
The earlier bug, which Guan reported and detailed in December 2025, was ultimately assigned a CVE tracker - CVE-2025-66479 - and patched in v0.0.16.
But the CVE only applies to Anthropic's sandbox-runtime, an upstream package, and not specifically to Claude Code, which Guan says means users have no way to know if their AI coding assistant is reading “allow nothing” as “allow everything.” He requested a CVE for Claude Code, and Anthropic said no because “The root cause is in the library.”
Guan told us he’s glad Anthropic ultimately addressed the security holes. But the entire disclosure process illustrates another problem that researchers and The Reg vultures have reported with how AI vendors often handle vulnerabilities in their products: no CVEs issued, and if the flaw is fixed, it usually happens silently, with no public advisories. More often than not, the burden of securing AI agents and other systems gets pushed to the end users.
The users need to know the risk is real, and in many cases, they may never know.
“Some vendors issue CVEs and some do not,” Guan said. "I think either approach can be reasonable, but the advisory is a must. The users need to know the risk is real, and in many cases, they may never know. What the public often does not see is that vendors may reward researchers and silently patch the software, while end users never learn from release notes or public advisories that the risk existed.”
According to Guan, this shows why users need their own protections, either from a security company or user-controlled runtime isolation. But he said he does hope big tech “takes on the burden of clearly communicating” security issues with users.
“Because of that, I think companies should treat AI agents more like employees than ordinary software tools,” he told us. “Before hiring an employee, companies do background checks. Before giving them access to systems, they define permissions. The same discipline should apply to AI agents.” ®