10 mincritical
Langflow Exploited to Build Custom DDoS Gafgyt Botnets
Attackers are actively exploiting CVE-2025-3248, a critical RCE vulnerability in Langflow's code validation API, to deploy a customized Gafgyt DDoS bot on AI development servers. The bot uses a modified RC4 stream cipher for C2 communications and is optimized purely for network flooding attacks (UDP, TCP, HOLD, Junk). AI infrastructure is targeted due to high bandwidth availability, shadow IT deployment practices, and permissive egress filtering.
Sens:■ ImmediateConf:high
Showing defanged values
- filenamebot.x86_64Dropped Gafgyt DDoS bot binary saved to /tmp/ on compromised Langflow servers; executed directly after chmod +x.
- ip184[.]174[.]96[.]191Dual-purpose attacker infrastructure: serves as the malware staging server (port 8088/TCP HTTP download of bot.x86_64) and the C2 command server (port 1337/TCP encrypted traffic).
- sha1523ae28b0833f9a68f4264d16c803ca5fdc771b9ELF build ID (SHA1) of the customized Gafgyt DDoS bot binary.
- sha256e00d92ca28a2cfd75e96f71fc0408747f04942657fcab0f2a25ce79bc3ad23a8SHA256 hash of the customized Gafgyt DDoS bot ELF binary (bot.x86_64) dropped on compromised Langflow servers.
- urlhxxp://184[.]174[.]96[.]191:8088/bot[.]x86_64HTTP URL used by the Langflow exploit payload to download the Gafgyt bot binary to /tmp/bot_x86_64 on compromised hosts.
Detection / Hunteropenrouter
What Happened
Hackers are breaking into servers running Langflow, a popular tool for building AI applications, by exploiting a security flaw that lets them run arbitrary code. Once inside, they install a malicious program that turns the server into a weapon for launching denial-of-service attacks — flooding other websites with so much traffic that they crash. The malicious program is a modernized version of an older botnet tool called Gafgyt, but it has been upgraded with custom encryption to hide its communications from security tools. Organizations using Langflow or similar AI development tools should update their software immediately, restrict outbound network access, and isolate AI development environments from the rest of their network. This matters because AI servers typically have high bandwidth and powerful hardware, making them attractive targets for attackers who want to launch large-scale attacks.
Key Takeaways
- Attackers exploit CVE-2025-3248, an unauthenticated RCE in Langflow's /api/v1/validate/code endpoint, to execute arbitrary Python on AI development servers.
- The dropped payload is a stripped-down Gafgyt/BASHLITE DDoS bot variant with no persistence, cryptomining, or lateral movement — optimized purely for network flooding via UDP, TCP, HOLD, and Junk flood vectors.
- C2 communications use a modified RC4 cipher with a nonstandard S-box seed, two-phase KSA with hardcoded keys, and a modified PRGA with rolling counters — specifically designed to evade automated decryption tools.
- AI/LLM development environments are prime targets due to high bandwidth, shadow IT deployment patterns, and overly permissive egress filtering.
- A YARA signature targeting unique S-box seed bytes (0d b4 5b 02 a9 50 f7 9e) is recommended for detection.
Affected Systems
- Langflow visual framework for AI/LLM application development (versions vulnerable to CVE-2025-3248)
- Linux x86_64 systems hosting Langflow instances
Vulnerabilities (CVEs)
copy:
| CVE | Product | Severity | Description |
|---|---|---|---|
| CVE-2025-3248 | Langflow (code validation API endpoint /api/v1/validate/code) | Critical | Unauthenticated remote code execution via the code validation API endpoint that accepts and executes untrusted Python scripts without proper sandboxing. |
Attack Chain
- Initial Access: Attackers exploit CVE-2025-3248 in Langflow's /api/v1/validate/code endpoint to execute untrusted Python code via os.system()
- Delivery: Injected Python code uses wget to download bot.x86_64 from http://184.174.96.191:8088/bot.x86_64 to /tmp/bot_x86_64
- Execution: Binary is marked executable (chmod +x) and launched from /tmp; it daemonizes via clone() and closes stdio descriptors
- C2: Bot establishes encrypted C2 communication with 184.174.96.191 over port 1337/TCP using a modified RC4 stream cipher
- Impact: Bot receives commands to execute UDP, TCP, HOLD, or Junk flood DDoS attacks against targets using raw sendto system calls
Detection Availability
- YARA Rules: Yes
- Sigma Rules: No
- Snort/Suricata Rules: No
- KQL Queries: No
- Splunk SPL Queries: No
- EQL Queries: No
- Other Detection Logic: No
- Platforms: Akamai blog post
The article recommends deploying YARA signatures targeting the unique S-box seed bytes (0d b4 5b 02 a9 50 f7 9e) from the modified RC4 cipher. No full YARA rule body is provided in the article; the seed bytes and behavioral indicators are described for defenders to build their own signatures.
Detection Engineering Assessment
copy:
| Dimension | Rating | Rationale |
|---|---|---|
| EDR Visibility | Medium | The binary runs from /tmp and closes stdio descriptors, which may be visible to EDR. However, the lack of persistence mechanisms and lateral movement reduces the behavioral footprint. Process execution from /tmp and the clone() daemonization call are detectable if EDR monitors process creation and syscall activity. |
| Network Visibility | Medium | C2 traffic over port 1337/TCP and the HTTP download over port 8088 are detectable if egress filtering and network monitoring are in place. However, the modified RC4 encryption makes payload inspection difficult. AI environments often have permissive egress rules that reduce network visibility. |
| Detection Difficulty | Moderate | The initial exploit targets a specific API endpoint and the binary has identifiable hashes and a unique S-box seed byte sequence. However, the modified RC4 encryption complicates C2 traffic analysis, and AI development environments often lack proper monitoring and segmentation. |
Required Log Sources
- Web application logs (Langflow /api/v1/validate/code endpoint access)
- EDR process creation and file write events
- Network firewall egress logs (ports 1337 and 8088)
- DNS resolution logs
- System stdout/stderr capture
Hunting Hypotheses
copy:
| Hypothesis | Telemetry | ATT&CK Stage | FP Risk |
|---|---|---|---|
| Consider hunting for processes executing from /tmp that immediately close standard file descriptors and spawn child processes via clone(), as this matches the Gafgyt variant's daemonization behavior. | EDR process creation, syscall monitoring (clone, close) | Execution | Low — legitimate applications rarely daemonize from /tmp and close all stdio descriptors immediately. |
| Consider hunting for outbound TCP connections to port 1337 from AI development servers, as this is the C2 command port for this Gafgyt variant. | Network firewall logs, NetFlow data, EDR network connections | Command and Control | Low to Medium — port 1337 is non-standard for legitimate services but could be used by custom applications. |
| Consider hunting for HTTP requests to the Langflow /api/v1/validate/code endpoint containing Python os.system calls or wget commands, which would indicate exploitation of CVE-2025-3248. | Web application firewall logs, reverse proxy logs, Langflow application logs | Initial Access | Low — legitimate code validation requests should not contain os.system or wget invocations. |
| Consider hunting for the ASCII string 'come at me krebs rimasuta go BRRT' in process memory or stdout logs, as this is a unique fingerprint of this Gafgyt variant. | EDR memory scanning, stdout log capture, file string analysis | Execution | Very Low — this is a unique taunting string unlikely to appear in legitimate software. |
| Consider hunting for high-volume outbound UDP or TCP traffic from AI development servers, which could indicate active DDoS flooding by the bot. | NetFlow data, network traffic analysis, DDoS monitoring tools | Impact | Medium — AI training workloads can generate high network traffic, requiring baseline comparison. |
Control Gaps
- WAF rules may not inspect POST bodies to /api/v1/validate/code for malicious Python payloads
- Standard egress filtering may not block port 1337/TCP in AI development environments with permissive outbound rules
- Network segmentation between AI development environments and production networks may be absent or insufficient
- Automated C2 traffic decryption tools will fail against the modified RC4 cipher variant
- Vulnerability management may not cover rapidly deployed experimental AI tools like Langflow
Key Behavioral Indicators
- Process executing from /tmp directory that closes stdio descriptors and forks via clone()
- Outbound TCP connections to port 1337 from AI/LLM development servers
- HTTP requests to /api/v1/validate/code endpoint containing os.system or wget strings
- Presence of S-box seed bytes 0d b4 5b 02 a9 50 f7 9e in binary files on disk
- High-volume UDP/TCP sendto syscall patterns from a single process
- wget downloading ELF binaries to /tmp from external IP addresses
False Positive Assessment
Low — the combination of processes running from /tmp, outbound connections on port 1337, the unique ASCII banner string, and the specific S-box seed bytes provide highly specific indicators with minimal legitimate overlap.
Recommendations
Immediate Mitigation
defender takeaway
- Verify against your organization's incident response runbook and team escalation paths before acting. Consider patching Langflow deployments to versions that resolve CVE-2025-3248 immediately if any instances are internet-facing.
- If your EDR supports host isolation, consider isolating any Langflow servers showing signs of compromise (processes in /tmp, outbound connections to port 1337, or the presence of the identified SHA256 hash).
- Consider blocking outbound traffic to 184.174.96.191 on ports 8088 and 1337 at your perimeter firewall if your network architecture permits.
- Evaluate whether your WAF can inspect and block requests to /api/v1/validate/code containing os.system, wget, or similar dangerous Python function calls.
Infrastructure Hardening
- Consider implementing strict egress filtering for AI development environments, limiting outbound access to only required destinations and ports.
- Evaluate segmenting AI development environments from production networks using VLANs or microsegmentation if supported by your network architecture.
- If applicable, consider placing Langflow and similar AI orchestration tools behind a reverse proxy or WAF that enforces authentication and input validation.
- Consider deploying network-based DDoS detection monitoring on AI server subnets to identify flooding behavior.
User Protection
- Consider deploying YARA signatures targeting the S-box seed bytes (0d b4 5b 02 a9 50 f7 9e) on endpoints hosting AI development tools, if your EDR supports YARA scanning.
- Evaluate whether your endpoint protection can alert on ELF binaries executing from /tmp directories on Linux AI development servers.
- If your organization uses file integrity monitoring, consider adding /tmp directories on AI servers to monitored paths.
Security Awareness
- Consider raising awareness among AI/ML development teams about the risks of deploying experimental tools like Langflow without proper security controls.
- If your organization has a shadow IT discovery program, consider including AI/ML frameworks and tools in the scope of discovered and monitored applications.
- Consider incorporating guidance on network segmentation and egress filtering into existing AI/ML development security guidelines.
MITRE ATT&CK Mapping
MITRE ATT&CK Mapping7 techniques
Tactic
Initial Access
Tactic
Execution
Tactic
Command and Control
Tactic
Impact
Additional IOCs
- File Hashes:
523ae28b0833f9a68f4264d16c803ca5fdc771b9(SHA1) - ELF build ID (SHA1) of the customized Gafgyt DDoS bot binary.
- File Paths:
/tmp/bot_x86_64- Volatile path where the Gafgyt bot binary is downloaded and executed on compromised Langflow servers.
- Command Lines:
- Purpose: Download the Gafgyt bot binary from staging server, make it executable, and launch it | Tools:
wget,chmod| Stage: Execution
- Purpose: Download the Gafgyt bot binary from staging server, make it executable, and launch it | Tools:
- Other:
0d b4 5b 02 a9 50 f7 9e- Unique S-box seed byte sequence from the modified RC4 cipher used in the bot's C2 communications; recommended as a YARA signature target.come at me krebs rimasuta go BRRT- Taunting ASCII banner output to stdout by the Gafgyt bot variant upon startup; can be found in stdout logs or memory strings.
