CVE-2024-35246

Executive Summary

CVE-2024-35246 is a high-severity denial-of-service (DoS) vulnerability (CVSS 7.5) that can be triggered by an unauthenticated remote attacker sending a high volume of specially crafted packets repeatedly against an affected service. The affected vendor and product are currently undisclosed, and while a single source claims a patch exists, this has not been independently verified by other researchers or the vendor itself. Successful exploitation causes resource exhaustion, leading to service unavailability and potential cascading failures in dependent infrastructure.

Technical Analysis

The vulnerability mechanism described in the NVD entry — "an attacker may be able to cause a denial-of-service condition by sending many packets repeatedly" — points to a resource exhaustion flaw in packet-processing logic. Based on the vulnerability class, the affected component likely fails to properly enforce rate limits, connection queues, or memory allocation thresholds when flooded with network traffic.

Likely technical root causes:

1. Unbounded memory allocation: The application may allocate memory per packet without a cap. Repeated packet submission causes heap exhaustion (OOM condition), crashing the process or entire host.

2. CPU starvation via expensive parsing: Each packet may trigger a computationally expensive operation (e.g., decryption, decompression, or regex matching). An attacker sending thousands of packets per second causes the CPU to spend all cycles on these operations, starving legitimate requests.

3. Connection queue saturation: If the target is a TCP-based service, the vulnerability may stem from an incomplete TCP handshake queue that cannot expire entries properly. Repeated SYN packets fill the queue, preventing legitimate connections.

4. Uncontrolled event loop / worker thread exhaustion: Multi-threaded services that spawn a thread per packet without a concurrency limit will exhaust thread pools, making the service unresponsive.

Attack surface: Network-exposed services — any listening port that processes client-supplied data. This includes HTTP/HTTPS servers, database endpoints, IoT device management interfaces, or UDP-based services. The attack does not require authentication (per the CVSS vector: PR:N, AV:N).

Code-level perspective: The vulnerability pattern likely resembles an unbounded while(receive_packet()) { process(packet); } loop without a maximum packet rate, or a buffer that is appended to without checking free memory. A patch would introduce a rate limiter, a maximum packet queue depth, or periodic queue cleanup.

Exploitation Scenarios

Scenario 1: HTTP Flood Against a Public-Facing Web Server

1. Reconnaissance: The attacker first maps the target's network using Shodan or Censys to identify public-facing web servers. They confirm the target is reachable and identify the open port (e.g., 443/TLS or 80/HTTP).

2. Weaponization: The attacker crafts a script (Python with scapy, hping3, or HTTPing) that generates a high volume of valid HTTP GET requests to a resource-intensive endpoint (e.g., a search query or file-upload handler). The requests are sent repeatedly in a tight loop. Because the vulnerability triggers on repeated packets, the attacker does not need to spoof IPs or use reflection — a simple direct flood suffices.

3. Payload/Execution: The attacker runs the script. Each request forces the server to parse headers, allocate a response buffer, and perform application-level processing. With N requests per second, the server's memory and CPU are consumed. After 30–60 seconds, the server stops responding to legitimate requests. Response times increase exponentially, then drop to zero (connection timeouts).

4. Post-Exploitation Impact: The server becomes unavailable for legitimate users. If the server hosts an e-commerce platform or critical API, this causes business disruption. The DoS may persist for hours if the attacker continues the flood; recovery requires restarting the service or massive rate-limiting intervention.

Scenario 2: UDP Packet Amplification (if the service uses UDP)

1. Reconnaissance: Attacker identifies a UDP-based service (e.g., NTP, TFTP, or a custom IoT protocol) exposed on the target network.

2. Weaponization: Attacker uses a tool like hping3 --udp --flood or a custom script sending malformed UDP payloads to the target port. The service's packet-processing loop cannot handle the volume.

3. Execution: Packets are sent at 10,000+ packets/second. The service allocates memory for each packet's processing context without cleanup, causing memory exhaustion. The process dies, or the host enters an OOM-kill cycle.

4. Impact: The target service and potentially co-located services on the same host crash. Monitoring systems alert but are also affected if they depend on the same host.

Scenario 3: TCP SYN Queue Saturation

1. Reconnaissance: Attacker scans the target to confirm TCP port 443 is open and the service uses a standard TCP backlog queue.

2. Weaponization: Attacker uses hping3 -S -p 443 --flood to send millions of TCP SYN packets with spoofed source IPs. The service cannot complete the three-way handshake (since the spoofed IPs never send ACKs), filling the SYN backlog queue.

3. Execution: The service's accept queue is full; new legitimate connection attempts are dropped. The CPU is consumed handling SYN-ACK retransmissions.

4. Impact: Web application becomes completely unreachable for new sessions. Existing sessions continue until timeout. This is a "low-and-slow" DoS that defies simple rate-based detection.

Impact Assessment

Business impact: DoS of the affected service directly translates into revenue loss (for commercial SaaS), degraded user trust, and potential SLA breach penalties. For critical infrastructure (e.g., healthcare, utilities), this could have safety implications.

Affected systems: Any network-facing instance of the undisclosed product. Given the CVSS score of 7.5 (High), the vulnerability has a significant impact on availability but does not compromise confidentiality (C:N) or integrity (I:N) according to the scoring vector.

Blast radius: Direct impact is on the single affected service. However, in microservices architectures, a single service being unavailable can cascade to dependent services, causing partial or total application outage. The attack requires no privileges (PR:N) and no user interaction (UI:N), making it easily exploitable by any external actor.

CVSS breakdown: With AV:N (network-exploitable), AC:L (no special conditions), PR:N (no authentication), UI:N (no user interaction), and a high availability impact (A:H), this is a classic "trivial to exploit, devastating to availability" vulnerability.

Detection Guidance

Sigma Rule

title: High Volume Packet Flood - Possible CVE-2024-35246 Exploitation
id: 7f3d2a1c-5b4e-4c6d-9a8b-0e1f2a3b4c5d
status: experimental
description: Detects a high volume of packets from a single source IP to a single destination, which may indicate exploitation of CVE-2024-35246 DoS vulnerability.
author: Valters IT Security Team
date: 2024/05/20
logsource:
  category: network_connection
  product: firewall
  definition: Firewall logs with connection events enabled
detection:
  selection:
    event.category: network_connection
    destination.port: [80, 443]  # Adjust to monitored service ports
    source.ip: "*"
  condition: selection
  timeframe: 60s
  aggregation:
    field: source.ip
    condition: count(destination.ip) > 10000
falsepositives:
  - Legitimate load testing or scanning activities
  - High-traffic public services
level: high
tags:
  - attack.t1498
  - cve.2024-35246
  - impact.dos

YARA Rule

rule CVE_2024_35246_Packet_Flood_Artifacts
{
    meta:
        author = "ValtersIT SOC"
        description = "Detects suspicious packet payload patterns associated with high-volume DoS attempts targeting CVE-2024-35246"
        date = "2024-05-20"
        score = 70
        cve = "CVE-2024-35246"

    strings:
        // Common flood tool signatures
        $hping = "HPING" ascii nocase
        $scapy = "scapy" ascii nocase
        $udpflood = "UDP-FLOOD" ascii nocase
        
        // Repeated identical payload pattern (rapid-fire)
        $repeat1 = { 41 41 41 41 41 41 41 41 } // AAAA repeated - common padding
        
        // High-entropy filler indicating automated packet generation
        $filler = { 00 00 00 00 01 00 00 00 02 00 00 00 }

    condition:
        // Packet with flood tool indicators OR
        // Repeated pattern with flood context
        any of ($hping*) and filesize < 10KB
        or
        (any of ($repeat*) and 2 of ($filler*) and filesize < 50KB)
}

Suricata IDS Rule

alert ip any any -> any any (msg:"ET DOS Possible CVE-2024-35246 Packet Flood Attempt"; flow:to_server; threshold:type both, track by_src, count 5000, seconds 10; classtype:attempted-dos; reference:cve,2024-35246; sid:202435246; rev:1;)

Explanation: This rule triggers when a single source IP sends >5,000 packets to any destination within 10 seconds. The threshold keyword provides built-in rate-based detection. Adjust count and seconds to match your network baseline.

Elastic Detection

// Detection of burst traffic pattern consistent with DoS flooding
sequence by source.ip with maxspan=10s
  [network where event.category == "network" and network.direction == "outbound" and destination.port in (80, 443) and network.protocol == "tcp"]
  [network where event.category == "network" and network.direction == "outbound" and destination.port in (80, 443) and network.protocol == "tcp"]
  [network where event.category == "network" and network.direction == "outbound" and destination.port in (80, 443) and network.protocol == "tcp"]
| where network.packets > 500

Alternative (simpler event count approach):

any where event.category == "network" and network.packets > 1000

Splunk SPL Query

index=firewall sourcetype=firewall_logs
| where dest_port IN (80, 443)
| bucket _time span=1m
| stats count as event_count by src_ip, _time
| where event_count > 10000
| table _time src_ip event_count
| sort - event_count

Explanation: This searches firewall logs, buckets events by minute, and flags source IPs generating more than 10,000 events in one minute — a strong indication of a DoS flood. Adjust threshold and field names (dest_port, src_ip) to match your firewall's field naming.

Wazuh OSSEC Rule

<rule id="100352" level="12">
  <decoded>network_connection</decoded>
  <field name="srcip">!127.0.0.1</field>
  <description>Possible CVE-2024-35246 packet flood - high volume traffic from single source</description>
  <group>network_denial_service,</group>
  <if_sid>100001</if_sid>
  <options>no_full_log</options>
  <frequency>60</frequency>
  <timeframe>60</timeframe>
  <match>packet_count>10000</match>
</rule>

Mitigation & Patch Guidance

Patch confidence: 2/4 (CLAIMED) — a single source claims a patch exists, but this is NOT independently confirmed. Vendor identity is undisclosed. Treat the system as actively vulnerable.

Immediate mitigations (while patch status is unclear):

1. Network-level rate limiting: Deploy ingress rate limiting at the firewall or load balancer. Set a maximum packets-per-second per source IP (e.g., 500 pps) for the affected service's port.
2. TCP SYN cookies: If the service is TCP-based, enable SYN cookies to prevent SYN queue saturation.
3. Anycast/IP-based traffic filtering: Use cloud-based DDoS protection (e.g., Cloudflare, AWS Shield) to absorb volumetric attacks before they reach the origin.
4. Monitor resource usage: Alert on unusual CPU, memory, or connection queue spikes (as in the detection rules above).

Patch/upgrade steps (when available):

1. Identify the affected product. Since the vendor is unknown, audit your asset inventory for any products matching the NVD description (packet-processing services). Prioritize products that have not issued security advisories recently.
2. Subscribe to NVD alerts for CVE-2024-35246 to be notified when details are updated.
3. Once the vendor is disclosed, apply the patch or upgrade to the fixed version. Confirm the patch with a second source (vendor advisory or independent researcher) before assuming it is valid.

Long-term hardening:

1. Defense in depth: Assume this class of vulnerability (unbounded packet processing) exists in other components. Implement generic rate-limiting and resource-quota controls across all network-facing services.
2. Regular vulnerability scanning: Include this CVE in your regular Nessus/Qualys/OpenVAS scan policies once vendor details are released.
3. Network segmentation: Reduce the attack surface by restricting access to critical services via firewall rules (allow only known IPs).
4. Incident response plan: Predefine a DoS playbook — including the orchestration of traffic rerouting and ISP-level null-routing — to minimize downtime during a flood attack.

References

1. NVD Entry: https://nvd.nist.gov/vuln/detail/CVE-2024-35246 — Official NVD record; current source for the (minimal) description and CVSS score. Monitor for updates as vendor is identified.
2. CVE.org Entry: https://cve.org/CVERecord?id=CVE-2024-35246 — CVE Record page; may contain CNA attribution updates.
3. FIRST.org CVSS Calculator: https://www.first.org/cvss/calculator/3.1#CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H — Reference for the CVSS 3.1 vector used above.
4. MITRE ATT&CK — T1498 (Network Denial of Service): https://attack.mitre.org/techniques/T1498/ — Tactic/technique taxonomy for this vulnerability class.
5. NVD Search/API: https://nvd.nist.gov/vuln/search/results?query=CVE-2024-35246 — Use to monitor for any new references, vendor advisories, or patch information as they are published.

Threat actor campaigns / exploit-in-the-wild evidence: As of this writing, there is no publicly reported exploit-in-the-wild activity, no CISA KEV listing, and no known threat actor campaigns targeting this CVE. The lack of public PoC, however, does not preclude active exploitation via private exploits — the "clusterf**k" of vendor secrecy means defenders should assume worst-case exposure.