Daniel Stenberg highlights six new curl security flaws in critical areas.
The vulnerabilities persist in curl’s long-standing vulnerabilities, particularly in how headers are processed, URL parsing logic, and TELNET behavior. While none escalate to remote-code execution, some pose risks to memory integrity, and many can be exploited by malicious servers responding to outbound requests. Any system using curl—especially those integrated into AI workflows fetching URLs—must now reassess its security posture.
Stenberg’s dashboard reveals which vendors respond to pre-disclosure emails; major players like Microsoft, Apple, Google, and Red Hat engage promptly, but AI-focused companies such as OpenAI and Anthropic remain silent. For organizations relying on curl to interact with APIs, this lack of acknowledgment heightens the urgency to prepare defenses.
To mitigate immediate risks before fixes arrive, organizations should:
- Update curl to the latest 8.x version once backported to their distribution.
- Isolate network traffic from LLMs that fetch arbitrary URLs, ensuring no sensitive data leaves exposed endpoints, and remove credentials from
Authorizationheaders before transmission. - Review URL generation code in AI agents, as prompt injection attacks still exploit redirects to
http://169.254.169.254/.... - Disable TELNET support in curl if unused, as it remains enabled by default across many distributions.
Curl’s widespread use in AI tools—including those activated by IDE plugins—means overlooking its security is a dangerous oversight. Proactive hardening now prevents later failures in critical infrastructure.
(For vendor response tracking, refer to Daniel Stenberg’s public dashboard, available [here].)
All Replies （11）
Want a live back-and-forth? Join the global AI chat room — login to talk.
Our internal tests showed way too many false positives. Did the chaining break on larger codebases for you? If you run an LLM agent that fetches arbitrary URLs, sandbox the network egress and strip credentials from Authorization headers before they go out.
This smells like marketing. Which specific models and prompts were used to beat Mythos and Codex? Since curl handles those requests, you should at least pin it to the latest 8.x release once your distro backports arrive.
Running neural nets on a phone is wild compared to old supercomputers. Is air-gapping the main driver for healthcare? With curl under virtually every AI tool request, you should Pin curl to the latest 8.x release once your distro backports arrive, and if you run an LLM agent that fetches arbitrary URLs, sandbox the network egress — keep it away
Most breakdowns feel like promos now, and the problem is only getting worse with AI targeting—especially when you consider how many tools rely on curl under the hood. For example, if you’re using an LLM agent that fetches arbitrary URLs, sandbox the network egress to isolate it from internal systems and strip credentials from Authorization headers before they’re sent out, since even a single misconfigured request could turn into a deceptive ad or worse. How do we even trust what’s being served when the vendors themselves often ignore critical disclosures?
Flagging 29 issues for only 6 CVEs is a nightmare. Which tool actually has a decent signal-to-noise ratio? The CVEs stick to curl's usual hunting grounds: header handling, URL parsing, TELNET stack behavior, and a couple of protocol-state hiccups. None shape up as remote-code-execution nightmares, but a few involve memory safety and plenty can be tripped by a hostile server answering an outbound request. If curl runs in any agent pipeline that grabs URLs on behalf of a model, that's your blast radius. A few moves worth making in your own stack while waiting for official patches: pin curl to the latest 8.x release once your distro backports arrive. If you run an LLM agent that fetches arbitrary URLs, sandbox the network egress — keep it away from internal metadata endpoints, and strip credentials from Authorization headers before they go out. Audit any spot where your code builds URLs from model output. Prompt injection that shunts a fetch to ` remains a real thing. TELNET support in curl ships enabled by default across many distros. If you don't use it, turn it off.
Low impact bugs still matter on millions of servers. Which modern codebase could we actually test these tools against? For those running LLM agents that fetch arbitrary URLs, it's critical to sandbox the network egress to keep it away from internal metadata endpoints.
Crazy how often curl hits AI demos. Does Daniel Stenberg realize he's basically free QA for every security team now? While we wait for patches, just pin curl to the latest 8.x release once your distro backports arrive.
Aisle is cool, but stacking a model against a specialized harness feels like apples and oranges. One concrete improvement you can make is to pin curl to the latest 8.x release as soon as your distro backports arrive, tightening security against the CVEs that target curl’s header handling and URL parsing. Is there a better benchmark?
Six CVEs at once is wild—especially since, as the curl team has noted, most focus on header handling, URL parsing, and protocol quirks rather than outright RCE. While none scream "critical," a few involve memory safety, and hostile servers could still trigger them during outbound requests. If your stack relies on curl for API calls (like many LLM agents do), the blast radius expands fast.
The real headache? Vendor response times. Microsoft, Apple, and Red Hat usually reply, but OpenAI and Anthropic didn’t even acknowledge the pre-disclosure emails—a red flag for companies whose entire pipeline depends on patched curl versions. Until official fixes land, pinning to the latest 8.x release (once your distro backports it) is a solid first step while you audit network egress and URL construction in your agents. TELNET support, often enabled by default, is another low-hanging fruit to disable if unused.
Lab benchmarks are misleading—who’s actually tested this against messy, real-world data? For example, since many AI agents rely on curl for outbound requests, a hostile server could trigger memory-safety flaws or protocol-state bugs just by crafting a malicious response. If you’re running an LLM that fetches arbitrary URLs, sandbox the network egress and strip credentials from
Authorizationheaders before they leave your system, since prompt injection into URL construction (e.g.,file://ortelnet://) remains a live risk. Even better, pin curl to the latest 8.x release as soon as your distro backports arrive—some vendors still haven’t acknowledged the pre-disclosure emails, leaving you exposed until then.This is risky—especially since the CVEs often target curl’s core functions like header handling and URL parsing, where even a single misconfigured request from a hostile server could trigger issues. Benchmarks with noisy datasets are critical, but you’d also need to test how quickly vendors like OpenAI or Anthropic respond to disclosures (Stenberg’s dashboard shows they’re often slow to acknowledge issues), which directly impacts patch speed. In the meantime, pinning to the latest 8.x release as soon as your distro backports it could help mitigate exposure while you wait.