CVE-2026-79980: Zephyr RTOS: predictable DHCPv4 xid enables gateway/DNS hijack
MEDIUMZephyr RTOS's DHCPv4 client reused and incremented a predictable transaction ID instead of drawing a fresh random one per transaction, so an attacker on the same network segment can forge DHCP replies that the device accepts. A single forged reply can repoint the device's default gateway and DNS resolvers to attacker-controlled addresses, enabling traffic interception, or force a lease drop. The AI relevance is indirect: Zephyr runs on edge and IoT devices that may host TinyML inference or feed AI pipelines, so hijacked traffic could poison or intercept their data. Severity is medium (CVSS 5.6, high attack complexity, adjacent-network positioning needed); EPSS is unavailable, it is not in CISA KEV, and no public exploit or Nuclei template exists. Apply the upstream Zephyr patch (commit 6a96770) in firmware builds, segment IoT and edge networks, and enable DHCP snooping on switches in the meantime.
What is the risk?
Medium overall. Exploitation needs network adjacency or a position on a previously joined network, plus knowledge of the xid, which is easy to obtain by sniffing the broadcast DHCPDISCOVER. No authentication or user interaction is needed, and one accepted datagram changes gateway and DNS settings. There is no known exploitation, no public exploit and no KEV listing. AI-specific exposure is limited to edge or embedded devices running Zephyr that perform on-device inference or telemetry collection. The package is not in the tracked AI package list and the dependent count is unknown.
How does the attack unfold?
What systems are affected?
| Package | Ecosystem | Vulnerable Range | Patched |
|---|---|---|---|
| zephyr | — | — | No patch |
Do you use zephyr? You're affected.
How severe is it?
What is the attack surface?
What should I do?
1 step1) Upgrade to a Zephyr build that includes commit 6a96770a1ea8c38a54a45f892c3e97be0f7dac41 (see advisory GHSA-p2q6-38x2-wmc8) and rebuild and redeploy device firmware. 2) Enable DHCP snooping and dynamic ARP inspection on switches, and restrict DHCP replies to trusted server ports. 3) Place embedded and edge AI devices on isolated VLANs with static addressing where feasible. 4) Require TLS with certificate validation and signed model and firmware updates, so a redirected gateway or DNS cannot serve tampered artifacts. 5) Detect rogue DHCP offers, unexpected gateway or DNS changes on devices, and unusual DHCPNAK traffic.
How is it classified?
Which compliance frameworks are affected?
This CVE is relevant to:
Frequently Asked Questions
What is CVE-2026-79980?
Zephyr RTOS's DHCPv4 client reused and incremented a predictable transaction ID instead of drawing a fresh random one per transaction, so an attacker on the same network segment can forge DHCP replies that the device accepts. A single forged reply can repoint the device's default gateway and DNS resolvers to attacker-controlled addresses, enabling traffic interception, or force a lease drop. The AI relevance is indirect: Zephyr runs on edge and IoT devices that may host TinyML inference or feed AI pipelines, so hijacked traffic could poison or intercept their data. Severity is medium (CVSS 5.6, high attack complexity, adjacent-network positioning needed); EPSS is unavailable, it is not in CISA KEV, and no public exploit or Nuclei template exists. Apply the upstream Zephyr patch (commit 6a96770) in firmware builds, segment IoT and edge networks, and enable DHCP snooping on switches in the meantime.
Is CVE-2026-79980 actively exploited?
No confirmed active exploitation of CVE-2026-79980 has been reported, but organizations should still patch proactively.
How to fix CVE-2026-79980?
1) Upgrade to a Zephyr build that includes commit 6a96770a1ea8c38a54a45f892c3e97be0f7dac41 (see advisory GHSA-p2q6-38x2-wmc8) and rebuild and redeploy device firmware. 2) Enable DHCP snooping and dynamic ARP inspection on switches, and restrict DHCP replies to trusted server ports. 3) Place embedded and edge AI devices on isolated VLANs with static addressing where feasible. 4) Require TLS with certificate validation and signed model and firmware updates, so a redirected gateway or DNS cannot serve tampered artifacts. 5) Detect rogue DHCP offers, unexpected gateway or DNS changes on devices, and unusual DHCPNAK traffic.
What systems are affected by CVE-2026-79980?
This vulnerability affects the following AI/ML architecture patterns: Edge AI / TinyML inference devices, IoT sensor gateways feeding ML pipelines, Embedded RTOS-based AI endpoints.
What is the CVSS score for CVE-2026-79980?
CVE-2026-79980 has a CVSS v3.1 base score of 5.6 (MEDIUM). The EPSS exploitation probability is 0.17%.
What is the AI security impact?
Affected AI Architectures
MITRE ATLAS Techniques
AML.T0029Denial of AI ServiceAML.T0049Exploit Public-Facing ApplicationCompliance Controls Affected
What are the technical details?
Original Advisory
The DHCPv4 client in subsys/net/lib/dhcpv4/dhcpv4.c maintained its transaction identifier (iface->config.dhcpv4.xid) as a counter rather than as a per-transaction random value. It was seeded once with sys_rand32_get() in dhcpv4_start_internal(), incremented by one in dhcpv4_send_discover() and dhcpv4_send_decline(), and never changed by dhcpv4_send_request() — so every RENEWING and REBINDING exchange reused, unchanged, the identifier that had already appeared on the wire in the broadcast DHCPDISCOVER at boot, and where the identifier did move it moved predictably by one. RFC 2131 4.1 requires a single identifier per transaction, chosen so that clients are unlikely to collide. This identifier is the client's only unpredictable reply-validation token. net_dhcpv4_input() accepts a BOOTP reply on op, a matching xid, and a matching chaddr (the interface MAC, which is public); the UDP callback is registered with a wildcard remote address and port, and no server-identifier or source-address check is applied. An attacker who learns one identifier — for example any host on the same segment that sees the broadcast DHCPDISCOVER, or a DHCP server or relay on a network the device previously joined — therefore retains a valid token for the device's whole uptime, and can predict the identifiers of later exchanges, without having to observe the unicast renew traffic or race the legitimate server. A forged reply that passes those checks has effect regardless of client state, because dhcpv4_parse_options() applies its side effects before the state machine gate in dhcpv4_handle_reply(): the router option calls net_if_ipv4_set_gw() and the DNS option calls dns_resolve_reconfigure(). A single accepted datagram can thus repoint the device's default gateway and resolvers at attacker-controlled addresses, redirecting its traffic; during RENEWING or REBINDING a forged DHCPACK re-binds the lease with attacker-chosen parameters and a forged DHCPNAK removes the address and restarts configuration. The fix draws a fresh sys_rand32_get() value at each point where a transaction begins — entering SELECTING, RENEWING and REBINDING, and at the INIT/INIT-REBOOT entry taken when an interface with a lease goes down — while REQUESTING and DECLINE keep the identifier of the exchange they belong to, as RFC 2131 requires. As a side effect the client also no longer discards a slow server's offer after retransmitting a discover, and the initial-discover backoff now draws its own randomness instead of deriving it from the identifier.
Exploitation Scenario
An attacker joins the same network segment as a fleet of Zephyr-based edge devices running on-device ML inference. They passively capture the broadcast DHCPDISCOVER to learn the xid, which is reused for later renew and rebind exchanges. They then send a forged DHCP reply with the correct xid and the device's MAC address, setting the gateway and DNS server to attacker-controlled hosts. The devices now route cloud API calls, telemetry and model update checks through the attacker, who can intercept data, serve spoofed responses or drop service.
Weaknesses (CWE)
CWE-340 — Generation of Predictable Numbers or Identifiers: The product uses a scheme that generates numbers or identifiers that are more predictable than required.
Source: MITRE CWE corpus.
CVSS Vector
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:L/A:LReferences
Timeline
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