Raw vector
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:HSummary
CVE-2025-59529 is a medium-severity Uncontrolled Resource Consumption (CWE-400) vulnerability in Avahi Avahi. Its CVSS base score is 5.5 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Application Exhaustion Flood (T1499.003); ranked at the 5th 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-10 (Concurrent Session Control) and SC-6 (Resource Availability) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-204402
Vulnerability Data
Avahi is a system which facilitates service discovery on a local network via the mDNS/DNS-SD protocol suite. In versions up to and including 0.9-rc2, the simple protocol server ignores the documented client limit and accepts unlimited connections, allowing for easy…
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local DoS. Although `CLIENTS_MAX` is defined, `server_work()` unconditionally `accept()`s and `client_new()` always appends the new client and increments `n_clients`. There is no check against the limit. When client cannot be accepted as a result of maximal socket number of avahi-daemon, it logs unconditionally error per each connection. Unprivileged local users can exhaust daemon memory and file descriptors, causing a denial of service system-wide for mDNS/DNS-SD. Exhausting local file descriptors causes increased system load caused by logging errors of each of request. Overloading prevents glibc calls using nss-mdns plugins to resolve `*.local.` names and link-local addresses. As of time of publication, no known patched versions are available, but a candidate fix is available in pull request 808, and some workarounds are available. Simple clients are offered for nss-mdns package functionality. It is not possible to disable the unix socket `/run/avahi-daemon/socket`, but resolution requests received via DBus are not affected directly. Tools avahi-resolve, avahi-resolve-address and avahi-resolve-host-name are not affected, they use DBus interface. It is possible to change permissions of unix socket after avahi-daemon is started. But avahi-daemon does not provide any configuration for it. Additional access restrictions like SELinux can also prevent unwanted tools to access the socket and keep resolution working for trusted users.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Local resource exhaustion via unlimited client connections directly enables Application Exhaustion Flood (T1499.003).
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Directly enforces a hard limit on concurrent client sessions, which the vulnerable server_work()/client_new() path fails to apply against CLIENTS_MAX.
Requires allocation of resources by quota or safeguard, preventing the unbounded file-descriptor and memory exhaustion that the missing limit check enables.
Mandates safeguards against denial-of-service via resource exhaustion on local IPC interfaces such as the avahi unix socket.
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.
Explicitly requires monitoring and maintaining resource capacity, directly addressing uncontrolled consumption to preserve availability.
Continuous monitoring of computing resources can detect resource exhaustion but does not itself enforce allocation limits.
Resilience mechanisms such as avoiding single points of failure indirectly reduce impact of resource exhaustion.
Hardened configuration baselines can include resource quotas and limits that constrain consumption.
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.
Resource-utilization monitoring and alerting on bottlenecks or overloads limits the impact of denial-of-service or resource-exhaustion attacks.
By continuously monitoring utilization, stress-testing peak loads, and maintaining documented plans to scale or throttle resources, the control directly limits an attacker’s ability to drive a system into uncontrolled resource exhaustion.
Pre-agreed severity-based prioritization and resource allocation during incident triage reduce the likelihood that an attacker-induced resource exhaustion will overwhelm the organization before corrective action is taken.
Business-continuity plans that include resource-management controls reduce the likelihood that an attacker can trigger uncontrolled resource consumption by forcing the system into a degraded or fallback state.
Defining RTOs and capacity requirements for ICT services during business-impact analysis forces organizations to provision sufficient resources and throttling mechanisms, reducing the likelihood that an attacker can induce denial-of-service through uncontrolled resource consumption.
Early notification of anomalous resource consumption or system malfunctions enables throttling or isolation before availability is lost.