Compromise Software Dependencies and Development Tools (T1195.001)
Compromise Software Dependencies and Development Tools [T1195.001]
Last updated
Compromise Software Dependencies and Development Tools [T1195.001]
Last updated
Name: Compromise Software Dependencies and Development Tools
ID: T1195.001
Tactics:
Technique:
Compromise Software Dependencies and Development Tools (T1195.001) is a sub-technique within the MITRE ATT&CK framework, categorized under Supply Chain Compromise (T1195). This attack method involves adversaries infiltrating software dependencies, libraries, or development tools frequently utilized by organizations in their software development lifecycle. Attackers exploit the inherent trust placed in third-party components, embedding malicious code or backdoors into legitimate software packages or tools, thereby gaining unauthorized access or control over target systems and networks.
Attackers execute this sub-technique by compromising software dependencies or development tools that organizations rely upon during software development and deployment processes. The technical execution commonly involves:
Dependency Hijacking: Attackers register or claim abandoned or misspelled package names on public repositories (e.g., npm, PyPI, RubyGems), tricking developers into unknowingly integrating malicious packages.
Dependency Confusion: Adversaries upload malicious packages to public repositories with the same names as internal private packages, causing automated package managers to pull malicious packages instead of secure internal ones.
Direct Compromise of Development Tools: Attackers compromise widely-used Integrated Development Environments (IDEs), build servers, continuous integration/continuous deployment (CI/CD) systems, or testing tools by injecting malicious code or backdoors.
Tampering with Legitimate Libraries: Attackers compromise legitimate open-source software repositories by gaining unauthorized access to maintainers' accounts or exploiting vulnerabilities in hosting platforms, inserting malicious code into legitimate software libraries or dependencies.
Code Injection and Obfuscation: Malicious code is often carefully obfuscated and hidden within legitimate functionality, making detection difficult during code reviews or automated security scans.
Credential Theft via Compromised Tools: Maliciously altered development tools may harvest sensitive credentials, keys, and tokens used in the development environment, facilitating lateral movement or privilege escalation.
Real-world procedures typically involve careful reconnaissance and understanding of the victim's software development processes and dependency management strategies, allowing attackers to effectively target and compromise specific software components or tools.
This sub-technique is typically employed in various attack scenarios and stages, including:
Initial Access Stage: Attackers leverage compromised dependencies or tools to gain initial footholds into otherwise secure environments.
Persistence Stage: Malicious dependencies or compromised development tools can persist undetected within the software supply chain, providing long-term access to targeted environments.
Privilege Escalation and Credential Harvesting: Attackers exploit compromised development tools to escalate privileges by harvesting developer credentials, tokens, or SSH keys.
Software Distribution and Propagation: Attackers embed malicious code into widely distributed software updates or releases, maximizing the number of victim organizations affected.
Espionage and Data Exfiltration: Nation-state adversaries frequently use compromised dependencies or tools to conduct espionage, gathering sensitive intellectual property, proprietary source code, or sensitive data from targeted organizations.
Detection methods for compromised software dependencies and development tools include:
Dependency Audits and Monitoring:
Regularly auditing third-party software dependencies using automated vulnerability scanners (e.g., Dependency-Check, OWASP Dependency Track).
Monitoring dependency repositories for unusual changes, updates, or suspicious package maintainers.
Integrity Verification:
Implementing cryptographic hashing and digital signatures to verify software integrity before integration into the development pipeline.
Behavioral Analysis and Sandboxing:
Employing sandbox environments or behavioral analysis tools to identify unusual behavior in software dependencies or development tools.
Code Review and Static Analysis:
Conducting thorough manual and automated code reviews, leveraging static code analysis tools to identify suspicious or obfuscated code.
Anomaly Detection in CI/CD Pipelines:
Monitoring CI/CD pipeline logs and build artifacts for anomalous behavior, unexpected network connections, or unauthorized modifications.
Endpoint Detection and Response (EDR) and SIEM Tools:
Utilizing EDR and Security Information and Event Management (SIEM) solutions to detect suspicious activities, network connections, or file modifications originating from compromised tools or dependencies.
Indicators of Compromise (IoCs) associated with this technique include:
Unexpected outbound network connections from development environments.
Unusual or unauthorized package updates or new dependencies introduced without clear justification.
Suspicious or unknown maintainers suddenly contributing to widely-used dependency repositories.
Integrity verification failures due to altered cryptographic hashes or signatures.
Detection of obfuscated or encoded payloads within software dependencies.
Early detection of compromised software dependencies and development tools is critical due to the significant potential impacts on systems and networks, including:
Widespread Compromise: A single compromised dependency or tool can affect numerous organizations, exponentially increasing the attacker's reach.
Data Breaches and Intellectual Property Theft: Attackers can exfiltrate sensitive data, intellectual property, or trade secrets, causing severe financial and reputational damage.
Loss of Trust and Reputation: Organizations affected by supply chain compromises can suffer long-term reputational damage, loss of customer trust, and regulatory scrutiny.
Operational Disruption: Malicious code embedded within development tools or dependencies can disrupt critical business operations, leading to downtime and productivity losses.
Difficulty of Remediation: Once embedded within the software supply chain, malicious code can be difficult to remediate, requiring extensive audits, code reviews, and incident response efforts.
Detecting this technique early allows organizations to limit damage, remediate threats quickly, and maintain trust with customers and stakeholders.
Real-world examples illustrating the use of compromised software dependencies and development tools include:
SolarWinds Orion Attack (2020):
Attack Scenario: Attackers compromised the SolarWinds Orion software build system, embedding malicious code ("SUNBURST") into legitimate software updates.
Tools Used: Malicious backdoor embedded in Orion software updates, sophisticated obfuscation techniques, and advanced command-and-control (C2) infrastructure.
Impacts: Thousands of organizations compromised, including major U.S. government agencies and Fortune 500 companies; significant data exfiltration and espionage activities.
Event-Stream npm Package Incident (2018):
Attack Scenario: Attackers gained control of the "event-stream" npm package, injecting malicious code targeting cryptocurrency wallets.
Tools Used: Obfuscated malicious payload within legitimate npm package updates, dependency hijacking.
Impacts: Theft of cryptocurrency funds from developers who unknowingly installed the malicious version of the package.
Codecov Bash Uploader Incident (2021):
Attack Scenario: Attackers compromised Codecov's Bash Uploader script, inserting malicious code to exfiltrate sensitive environment variables (credentials, tokens) from CI/CD environments.
Tools Used: Maliciously modified Bash script, stealthy exfiltration of sensitive data.
Impacts: Numerous organizations affected, exposure of sensitive credentials, and potential unauthorized access to internal systems.
Dependency Confusion Attacks (2021):
Attack Scenario: Security researchers demonstrated successful "dependency confusion" attacks by registering malicious packages with identical names to internal packages, tricking automated package managers into downloading malicious code.
Tools Used: Malicious packages uploaded to public repositories (npm, PyPI), automated dependency resolution exploitation.
Impacts: Proof-of-concept attacks demonstrated potential widespread compromise, prompting organizations to review and strengthen dependency management practices.