Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:H/A:NCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2026-82209 is a high-severity Insertion of Sensitive Information Into Sent Data (CWE-201) vulnerability in Haxx Curl. Its CVSS base score is 8.2 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Network Sniffing (T1040); ranked at the 44th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
The strongest mitigations our analysis identified map to AC-3 (Access Enforcement) and AC-4 (Information Flow Enforcement) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-72153
Vulnerability Data
When libpsl support is enabled, libcurl fails to enforce the Public Suffix List boundary check when processing a `Set-Cookie` header where the `Domain` attribute explicitly matches an origin host that is itself a public suffix (e.g., `Domain=co.uk` set by `co.uk`).…
more
Instead of coercing it into a strict host-only cookie, libcurl saves the cookie with wildcard domain scope (`.co.uk`). Consequently, the cookie is inappropriately included in subsequent outbound requests or HTTP redirects to arbitrary sibling subdomains under the same public suffix (e.g., `attacker.co.uk`).
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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- 1 hardening rule · 1 OS baseline
V14.2.3
Mitigating Controls (NIST 800-53 r5) AI
Directly enforces policy-based information flow rules that block transmission of sensitive data to unauthorized actors.
Enforces authorizations on logical access so that sensitive data is not released to unauthorized recipients.
Requires validation of outbound information to ensure sensitive content is not disclosed in responses or messages.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Monitoring runtime data flows and outputs can detect sensitive data being transmitted.
Protecting data-in-transit can include filtering or encrypting to avoid exposing sensitive content.
Protecting data-in-use includes removing confidential values before they are processed or sent.
Secure SDLC practices directly prevent insertion of sensitive data into application outputs and messages.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Classification identifies sensitive data so it is not inadvertently transmitted.
Labelling makes sensitive data visible to developers and prevents accidental inclusion in outbound messages.
Information-transfer rules directly govern what data may be sent to external parties.
PII-protection requirements reduce the chance of sending personal data to unauthorized recipients.
Data-masking techniques can prevent sensitive values from appearing in transmitted payloads.
DLP controls inspect and block outbound flows that contain sensitive information.