Python Infostealer Exposes New Clipboard Image Attack Vector in 2024
Executive Summary
In October 2024, a new Python-based infostealer was discovered leveraging the clipboard’s picture functionality to stealthily exfiltrate screenshots and images from victim machines. The malware, observed in the wild using Telegram for command-and-control, exploits the common trust in clipboard features by targeting not only text but also graphical data such as screenshots often exchanged for reporting or documentation. Notably, the malware’s code contained Vietnamese-language comments, and a sample analyzed had a low detection score on VirusTotal, indicating low awareness and potential for widespread impact.
This incident highlights the evolution of infostealer tactics as they expand data theft payloads beyond credentials and text, exploiting overlooked vectors like clipboard images. Such techniques present new challenges for organizations as attackers increasingly focus on fileless, cross-platform exfiltration and abuse of trusted collaboration workflows.
Why This Matters Now
As remote and hybrid workforces rely heavily on clipboard sharing and image-based workflows, attackers exploiting clipboard image access demonstrate innovative data theft techniques. This rapidly emerging attack vector can bypass legacy monitoring and is under-detected, intensifying the urgency for enhanced endpoint security and tighter clipboard controls.
Attack Path Analysis
The attacker gained initial access by delivering a Python-based infostealer onto a user's system, potentially via phishing or compromised downloads. No privilege escalation activity was explicitly observed, but the malware operated with whatever access it had. Lateral movement was not detected, as the infostealer targeted clipboard data on a single machine. The malware established command and control through outbound Telegram API communications, uploading clipboard images when available. Clipboard images and potentially sensitive data were exfiltrated via this C2 channel. The overall impact of the attack was covert exfiltration of screenshots or sensitive images, risking confidential data leakage.
Kill Chain Progression
Initial Compromise
Description
The infostealer malware was delivered and executed on the user's system, potentially via phishing or malicious download.
MITRE ATT&CK® Techniques
Clipboard Data
Data from Local System
Exfiltration Over Web Service: Exfiltration to Cloud Storage
User Execution: Malicious File
Application Layer Protocol: Web Protocols
Non-Application Layer Protocol
Input Capture: Screen Capture
Obfuscated Files or Information
Potential Compliance Exposure
Mapping incident impact across multiple compliance frameworks.
PCI DSS 4.0 – Protection of Sensitive Data
Control ID: 3.2.1
NYDFS 23 NYCRR 500 – Information Security Program
Control ID: 500.03
DORA (Digital Operational Resilience Act) – ICT Security Policies and Procedures
Control ID: Art. 8
CISA Zero Trust Maturity Model 2.0 – Data Use Control and Monitoring
Control ID: Data Pillar - Data Protection
NIS2 Directive – Technical and Organizational Measures
Control ID: Article 21(2) a
Sector Implications
Industry-specific impact of the vulnerabilities, including operational, regulatory, and cloud security risks.
Financial Services
Python infostealer targeting clipboard images threatens sensitive financial data, screenshots of transactions, trading information, and customer details through automated exfiltration via Telegram.
Health Care / Life Sciences
Clipboard image theft poses severe HIPAA compliance risks, potentially exposing patient records, medical images, and PHI shared through screenshots in healthcare workflows.
Government Administration
Infostealer's clipboard monitoring capability threatens classified documents, sensitive communications, and operational security through automated capture of government screenshot sharing practices.
Information Technology/IT
IT professionals face significant risk from clipboard image exfiltration targeting system configurations, network diagrams, and technical documentation commonly shared via screenshots.
Sources
- Clipboard Pictures Exfiltration in Python Infostealer, (Wed, Oct 15th)https://isc.sans.edu/diary/rss/32372Verified
- Clipboard Pictures Exfiltration in Python Infostealerhttps://isc.sans.edu/diary/Clipboard%2BPictures%2BExfiltration%2Bin%2BPython%2BInfostealer/32372Verified
- Snake Infostealer Malwarehttps://www.cybereason.com/blog/research/threat-analysis-report-snake-infostealer-malwareVerified
- Threat Actor Distributes Python-Based Information Stealer Using a Fake Falcon Sensor Update Lurehttps://www.crowdstrike.com/en-us/blog/threat-actor-distributes-python-based-information-stealer/Verified
Frequently Asked Questions
Cloud Native Security Fabric Mitigations and ControlsCNSF
Applying Zero Trust segmentation, strict egress controls, and threat detection would have restricted malware communication, visibility, and exfiltration pathways. CNSF capabilities like Egress Security, Inline IPS, and centralized visibility could have identified and disrupted infostealer actions at key points in the attack chain.
Control: Threat Detection & Anomaly Response
Mitigation: Early detection and alerting on anomalous or malicious file activity.
Control: Zero Trust Segmentation
Mitigation: Limits malware's access based on identity and least privilege.
Control: East-West Traffic Security
Mitigation: Prevents or detects unauthorized lateral spread attempts.
Control: Egress Security & Policy Enforcement
Mitigation: Blocks unauthorized outbound communications to suspicious domains like Telegram APIs.
Control: Inline IPS (Suricata)
Mitigation: Detects and prevents known malicious payloads and exfiltration attempts.
Improved auditability and rapid incident response capability post-compromise.
Impact at a Glance
Affected Business Functions
- Data Security
- Compliance
- Intellectual Property Protection
Estimated downtime: 3 days
Estimated loss: $50,000
Potential exposure of sensitive information such as credentials, intellectual property, and personal data through clipboard image exfiltration.
Recommended Actions
Key Takeaways & Next Steps
- • Enforce Zero Trust segmentation and least privilege policies at the network and workload level to minimize malware impact.
- • Deploy egress filtering to block unauthorized outbound communications, especially to known threat actor C2 domains like Telegram APIs.
- • Implement Inline IPS and threat detection capabilities to identify anomalous processes or exfiltration activity in real time.
- • Improve centralized visibility across multicloud environments for faster detection, investigation, and response to suspicious traffic.
- • Regularly monitor clipboard sharing settings, especially in virtualized or hybrid environments, and educate staff on risks of clipboard-based data exposure.
