Cyber Attribution

In the context of cybersecurity, cyber attribution is the complex process of identifying the perpetrator(s) behind a cyberattack or malicious cyber activity. It goes beyond simply identifying the compromised systems or the methods used in an attack; the ultimate goal is to determine who is responsible.

This "who" can range from:

• Individuals: Lone hackers or insiders.

• Criminal Groups: Organized cybercrime syndicates.

• State-Sponsored Actors (Advanced Persistent Threats - APTs): Groups acting on behalf of a nation-state, often with significant resources and sophisticated tactics.

• Hacktivists: Groups driven by political or social agendas.

Why is Cyber Attribution Crucial?

Cyber attribution is vital for several reasons:

1. Accountability and Justice: It enables legal, diplomatic, or punitive actions to be taken against perpetrators. Without attribution, it's challenging to hold anyone responsible for the damage caused.

2. Deterrence: When attackers know they can be identified, it acts as a deterrent, making them less likely to launch future attacks. Public attribution, especially by governments, sends a strong message.

3. Improved Defenses: Understanding who is behind an attack and their motivations helps organizations and governments better understand their adversaries. This intelligence allows for the development of more targeted and effective defensive strategies by analyzing their tactics, techniques, and procedures (TTPs).

4. Strategic Response: For nation-states, attribution is a critical element in developing appropriate political, economic, or even military responses to cyberattacks that may be considered acts of aggression or espionage.

5. Intelligence Gathering: Attributing an attack can provide valuable insights into an adversary's capabilities, goals, and methods, which can then be used to anticipate future threats.

The Complexity and Challenges of Cyber Attribution

Despite its importance, cyber attribution is incredibly challenging due to the inherent nature of cyberspace:

• Anonymity and Obfuscation: Attackers frequently employ techniques such as IP spoofing, routing attacks through multiple compromised systems (botnets, proxy chains), Virtual Private Networks (VPNs), and The Onion Router (TOR) to conceal their proper location and identity.

• Lack of Physical Evidence: Unlike traditional crime scenes, cyberattacks leave digital traces that can be manipulated, erased, or misleading.

• False Flags: Skilled adversaries may intentionally leave false clues or use methods associated with other known groups to mislead investigators and deflect blame. This makes it difficult to assign responsibility definitively.

• Shared Tools and Techniques: The increasing availability of "off-the-shelf" malware and hacking tools means that different groups, even those unrelated, might use similar attack methods, making it harder to distinguish between them based solely on technical indicators.

• Jurisdictional Issues: Cyberattacks often cross international borders, complicating investigations and legal responses due to differing laws and limited international cooperation.

• Time and Resource Intensive: Attribution requires extensive cyber forensic analysis, often involving significant resources, expertise, and time to collect and analyze vast amounts of data.

• Levels of Attribution: Attribution can exist on multiple levels, ranging from attributing an attack to a specific machine or human operator to an ultimately responsible party (e.g., a criminal organization or nation-state). Each level requires different types and amounts of evidence.

Methods and Techniques for Cyber Attribution

Cybersecurity professionals use a combination of technical, behavioral, and intelligence-based methods for attribution:

• Technical Analysis:

  • Malware Analysis: Examining the code, functionality, and unique "fingerprints" of malware used in an attack can link it to known threat actors who use similar tools or development practices.

  • Network Forensics: Analyzing network traffic, command-and-control (C2) server communications, and log files to trace the attack's origin and infrastructure.

  • Indicators of Compromise (IoCs): Identifying malicious IP addresses, domain names, file hashes, and other artifacts known to be associated with specific threat actors.

• Behavioral Analysis (TTPs):

  • Tactics, Techniques, and Procedures (TTPs): Analyzing the specific methods, tools, and operational patterns used by the attackers. Threat intelligence frameworks like MITRE ATT&CK are crucial here, helping to compare new attacks with the established TTPs of known groups. For example, specific entry points, lateral movement techniques, or data exfiltration methods can be characteristic of certain actors.

  • Language and Cultural Cues: In some cases, analysis of code comments, metadata, or communication patterns can provide hints about the geographical or cultural origin of the attackers.

• Contextual and Threat Intelligence:

  • Threat Actor Profiles: Cybersecurity organizations maintain extensive databases of known threat actors, including their motivations, capabilities, past campaigns, and geopolitical affiliations. Correlating data from a new attack with these profiles is a key part of attribution.

  • Open-Source Intelligence (OSINT) and Human Intelligence (HUMINT): Gathering information from publicly available sources (social media, news, forums) and, for government agencies, classified human intelligence, to build a broader picture of the adversary.

  • Geopolitical Context: Understanding the political and economic landscape can help in identifying potential state-sponsored actors and their motives.

Legal and Policy Implications

Attribution has significant legal and policy implications, particularly at the state level. International law, while still evolving in the cyber domain, suggests that a state can be held responsible for cyberattacks if:

• The operation is carried out by state organs (e.g., military, intelligence agencies).

• Non-state actors conduct the attack under the direction or control of a state.

• A state acknowledges and adopts the wrongful act.

However, the lack of a universal legal framework, the difficulty of providing definitive technical evidence that is legally admissible, and the challenges of achieving international consensus on what constitutes an "armed attack" in cyberspace continue to complicate legal accountability for cyberattacks.

Cyber attribution is a multifaceted and challenging endeavor in cybersecurity that aims to identify the perpetrators of malicious cyber activity definitively. It combines advanced technical analysis, behavioral profiling, and extensive intelligence gathering to provide crucial insights for defense, deterrence, and appropriate response.

ThreatNG, as an all-in-one external attack surface management, digital risk protection, and security ratings solution, provides comprehensive capabilities that directly assist in cyber attribution efforts. Its strength lies in gathering crucial external intelligence that can help identify and understand the adversary.

External Discovery

ThreatNG excels at purely external, unauthenticated discovery, meaning it can map out an organization's digital footprint from an attacker's perspective without needing any internal connectors. This capability is fundamental to attribution as it reveals the external-facing assets that an attacker would likely target or use in an attack. By understanding an organization's public-facing infrastructure, ThreatNG can help identify potential initial access vectors, which are critical clues in an attribution investigation.

External Assessment

ThreatNG performs various external assessments that provide deep insights into an organization's vulnerabilities and exposures, indirectly aiding attribution by revealing patterns or specific weaknesses exploited by attackers.

• Web Application Hijack Susceptibility: ThreatNG analyzes external parts of web applications to identify potential entry points for attackers, using domain intelligence. If an attack involves web application compromise, this assessment can pinpoint the likely attack vector, narrowing down the scope of investigation and potentially linking it to attacker TTPs.

• Subdomain Takeover Susceptibility: This assessment evaluates a website's susceptibility to subdomain takeover by analyzing subdomains, DNS records, and SSL certificate statuses. If a subdomain takeover is part of an attack chain, ThreatNG's assessment can confirm the vulnerability and provide technical details that might match known attacker behaviors.

• BEC & Phishing Susceptibility: Derived from sentiment, financials, domain intelligence (including domain name permutations and Web3 domains), and email intelligence (email security presence and format prediction), as well as dark web presence of compromised credentials, this assessment helps understand an organization's susceptibility to business email compromise and phishing. If an attack originated from a phishing campaign, ThreatNG's insights into email security posture and compromised credentials could help explain how the initial breach occurred and potentially link it to specific phishing kits or techniques.

• Brand Damage Susceptibility: This assessment utilizes attack surface intelligence, digital risk intelligence, ESG violations, sentiment analysis, financial data (including lawsuits, SEC filings, and SEC Form 8-Ks), and domain intelligence to determine brand damage susceptibility. While less direct for technical attribution, understanding an attacker's motivation (e.g., reputational damage) can sometimes narrow down the pool of potential adversaries.

• Data Leak Susceptibility: ThreatNG assesses this based on cloud and SaaS exposure, dark web presence (including compromised credentials), domain intelligence (DNS and email intelligence), and sentiment/financials (including lawsuits and SEC Form 8-Ks). If an attack results in a data leak, this assessment can identify the most probable sources of the leak, such as exposed cloud buckets or compromised credentials, which are crucial for tracing the exfiltration path and potentially the attacker's methods.

• Cyber Risk Exposure: This score considers certificates, subdomain headers, vulnerabilities, and sensitive ports covered by the Domain Intelligence module. It also factors in code secret exposure by discovering code repositories and their content for sensitive data, cloud and SaaS exposure, and compromised credentials on the dark web. This comprehensive view of cyber risk exposure can reveal specific vulnerabilities (e.g., exposed sensitive ports, unpatched vulnerabilities) that attackers might have exploited for initial access or lateral movement, providing crucial technical indicators for attribution. For example, if an attacker exploited a specific CVE, ThreatNG's assessment would have highlighted that vulnerability, linking the attack back to a known exploit used by certain threat groups.

• ESG Exposure: ThreatNG rates an organization based on discovered environmental, social, and governance (ESG) violations through its external attack surface and digital risk intelligence findings, analyzing areas like competition, consumer, and employment-related offenses. While not directly technical, an attacker's motivation (e.g., hacktivism targeting specific ESG violations) could be inferred from this data, aiding in non-technical attribution.

• Supply Chain & Third Party Exposure: This is derived from Domain Intelligence (enumeration of vendor technologies from DNS and subdomains), Technology Stack, and Cloud and SaaS Exposure. If a cyberattack originates from a supply chain compromise, ThreatNG can identify exposed third-party technologies or cloud services, helping to pinpoint the likely entry point through a trusted vendor.

• Breach & Ransomware Susceptibility: Calculated from external attack surface and digital risk intelligence, including domain intelligence (exposed sensitive ports, private IPs, vulnerabilities), dark web presence (compromised credentials, ransomware events and gang activity), and sentiment/financials (SEC Form 8-Ks). This is highly relevant to attribution for ransomware attacks, as it directly links to compromised credentials and known activities of ransomware groups, allowing investigators to identify the probable ransomware gang.

• Mobile App Exposure: ThreatNG evaluates how exposed an organization's mobile apps are by discovering them in marketplaces and analyzing their contents for access credentials (e.g., AWS Access Key ID, API keys, GitHub Access Token), security credentials (e.g., PGP private key, RSA Private Key), and platform-specific identifiers (e.g., S3 Buckets, Firebase). If a mobile app is identified as the entry point or source of a data leak, ThreatNG's findings on exposed credentials or sensitive information within the app would be critical for understanding the attack vector and potentially linking it to known mobile-focused threat actors.

Reporting

ThreatNG provides various reports, including executive, technical, and prioritized (High, Medium, Low, and Informational) reports, as well as security ratings, inventory, ransomware susceptibility, U.S. SEC Filings, and External GRC Assessment Mappings (PCI DSS and POPIA). These reports consolidate the assessment findings, which are invaluable for attribution. Technical reports can detail specific vulnerabilities, exposed assets, or compromised credentials, providing forensic data points. Prioritized reports help focus investigative efforts on the most critical exposures that might have been exploited.

Continuous Monitoring

ThreatNG offers continuous monitoring of external attack surface, digital risk, and security ratings for all organizations. This constant monitoring is crucial for attribution, as it provides a historical record of an organization's external security posture. By observing changes in the attack surface or sudden increases in risk, investigators can identify when and how a compromise might have occurred, track the evolution of an attack, and spot new attacker infrastructure or TTPs as they emerge. This persistent oversight enables earlier detection and faster response, which are crucial for effective attribution.

Investigation Modules

ThreatNG's investigation modules offer deep dives into specific areas, providing granular data essential for attribution:

• Domain Intelligence: This module provides a comprehensive overview of digital presence, including Microsoft Entra Identification, Domain Enumeration, Bug Bounty Programs, and related SwaggerHub instances.

  • DNS Intelligence: Includes domain record analysis (IP identification, vendors and technology identification), domain name permutations, and Web3 domains. For attribution, identifying unusual or newly registered domain name permutations associated with an organization, or discovering malicious Web3 domains, can point to attacker infrastructure used in phishing or C2 operations.

  • Email Intelligence: Provides insights into email security presence (DMARC, SPF, DKIM records) and harvested email addresses. This is crucial for BEC and phishing attribution, as it helps identify how attackers might have spoofed emails or harvested legitimate email addresses.

  • WHOIS Intelligence: Provides WHOIS analysis and other domains owned by the same entity. This can uncover connections between seemingly disparate malicious domains, potentially revealing an attacker's broader infrastructure.

  • Subdomain Intelligence: Analyzes HTTP responses, header analysis (security and deprecated headers), server headers, cloud hosting, e-commerce platforms, CMS, code repositories, and critical ports (e.g., IoT/OT, databases, remote access services). For example, discovering exposed sensitive ports (like Telnet or RDP) on a subdomain can indicate a likely entry point for an attacker, and the specific technology identified (e.g., a vulnerable CMS version) can be linked to known exploits used by certain threat groups. Identifying a subdomain takeover susceptibility can directly point to a specific type of attack method used.

• IP Intelligence: Covers IPs, shared IPs, ASNs, country locations, and private IPs. Tracing malicious activity back to specific IP addresses and then to their associated Autonomous System Numbers (ASNs) and country locations is a foundational step in cyber attribution, helping to geographically narrow down potential threat actors.

• Certificate Intelligence: Focuses on TLS Certificates (status, issuers, active, certs without subdomains, subdomains without certificates) and Associated Organizations. Anomalies in certificate usage or the issuance of new certificates for an organization can sometimes indicate attacker activity or malicious infrastructure.

• Social Media: Analyzes posts from the organization, breaking out content, hashtags, links, and tags. While less direct for technical attribution, this can provide insights into an attacker's motives if the attack is accompanied by public statements or propaganda on social media.

• Sensitive Code Exposure:

  • Code Repository Exposure: Discovers public code repositories and uncovers digital risks like exposed access credentials (e.g., Stripe API key, AWS Access Key ID, GitHub Access Token), security credentials (e.g., private cryptographic keys, SSH Private Key), configuration files (e.g., Azure service configuration, Jenkins publish over SSH plugin file), database exposures (e.g., SQL dump file, PostgreSQL password file), and application data exposures (e.g., remote desktop connection files, Java keystores). Suppose an attack involves the use of stolen credentials or exploitation of misconfigurations. In that case, ThreatNG's ability to find these exposures in public code repositories provides direct evidence of the initial compromise vector and links to specific attacker methods (e.g., scanning for exposed keys).

  • Mobile Application Discovery: Discovers mobile apps in marketplaces and identifies the presence of access credentials, security credentials, and platform-specific identifiers within them. If a mobile app is the source of a data breach, ThreatNG can identify the exposed sensitive information, aiding in forensic analysis and attribution.

• Search Engine Exploitation:

  • Website Control Files (Robots.txt, Security.txt): Discovers the presence and content of robots.txt (revealing secure directories, user directories, email directories, admin directories) and security.txt files (contact info, PGP key, bug bounty program). Anomalies or unexpected information in these files could be indicators of compromise or reconnaissance by an attacker.

  • Search Engine Attack Surface: Helps investigate susceptibility to exposing errors, sensitive information, public passwords, and susceptible files/servers via search engines. If an attacker uses search engine techniques (such as Google Dorking) to find vulnerabilities, ThreatNG can reveal what information is exposed, aiding in understanding the attacker's initial reconnaissance phase.

• Cloud and SaaS Exposure: Identifies sanctioned and unsanctioned cloud services, impersonations, and open exposed cloud buckets (AWS, Azure, GCP). It also lists exposed SaaS implementations. If an attack involves cloud misconfiguration or compromise of a SaaS application, ThreatNG can pinpoint the specific exposed services or buckets, helping to trace the origin and methods of the attack. For example, an open AWS S3 bucket could be the source of a data leak or an initial entry point.

• Online Sharing Exposure: Detects the presence of organizational entities on online code-sharing platforms, such as Pastebin and GitHub Gist. This is critical for attribution if attackers have exfiltrated data or shared information about the target on these platforms.

• Sentiment and Financials: Identifies lawsuits, layoff chatter, SEC filings (especially risk and oversight disclosures), SEC Form 8-Ks, and ESG violations. While not direct technical indicators, this can reveal motivations (e.g., financial gain, disruption) that help profile potential attackers.

• Archived Web Pages: Discovers archived files (APIs, documents, emails, login pages, user names, admin pages) from an organization's online presence. This can reveal historical vulnerabilities or expose sensitive information that attackers might have exploited.

• Dark Web Presence: Detects organizational mentions, associated ransomware events, and compromised credentials on the dark web. This is incredibly powerful for attribution, as it can directly link an attack to known compromised credentials, specific ransomware gangs, and their activities, providing strong evidence of the perpetrator.

• Technology Stack: Identifies all technologies used by the organization (e.g., CMS, databases, web servers). Knowing the technology stack allows investigators to identify specific vulnerabilities (CVEs) associated with those technologies that might have been exploited, thereby narrowing down the list of potential attack methods and linking them to known threat actors who exploit such vulnerabilities.

Intelligence Repositories (DarCache)

ThreatNG's continuously updated intelligence repositories, branded as DarCache, are highly valuable for cyber attribution:

• Dark Web (DarCache Dark Web): Provides direct intelligence on compromised credentials, ransomware groups, and their activities. This allows for rapid cross-referencing of attack indicators with known dark web activities, directly aiding in attributing attacks to specific criminal groups or ransomware gangs.

• Compromised Credentials (DarCache Rupture): Contains information on compromised credentials. If an attack uses stolen credentials, this repository can confirm if those credentials were previously compromised and where they appeared, helping to trace the initial breach.

• Ransomware Groups and Activities (DarCache Ransomware): Tracks over 70 ransomware gangs. This repository is a direct aid to attribution, allowing investigators to identify which ransomware group's TTPs match an ongoing or past attack, even if the ransomware itself is customized.

• Vulnerabilities (DarCache Vulnerability): Offers a holistic and proactive approach to managing external risks by understanding real-world exploitability, likelihood of exploitation, and potential impact.

  • NVD (DarCache NVD): Provides detailed information on CVEs, including attack complexity, vector, and impact scores (CVSS).

  • EPSS (DarCache EPSS): Offers a probabilistic estimate of the likelihood of a vulnerability being exploited.

  • KEV (DarCache KEV): Lists vulnerabilities actively being exploited in the wild.

  • Verified Proof-of-Concept (PoC) Exploits (DarCache eXploit): Provides direct links to PoC exploits on platforms like GitHub, referenced by CVE. These vulnerability intelligence sources are crucial for technical attribution. If an attack leverages a known vulnerability, ThreatNG can not only identify that vulnerability but also provide context on its exploitability and whether a PoC exists, helping to confirm if the attack method aligns with publicly known exploits favored by certain threat actors. For example, suppose an organization is hit by an attack exploiting a specific vulnerability listed in KEV. In that case, it strongly suggests the attacker is using a widely known and actively exploited flaw.

• ESG Violations (DarCache ESG): Lists various environmental, social, and governance offenses. This can aid in understanding the motivations of hacktivist groups that might target organizations based on these violations.

• Bug Bounty Programs (DarCache Bug Bounty): Details of in-scope and out-of-scope assets for bug bounty programs. This can help investigators determine if a vulnerability was reported via a legitimate bug bounty program or if it was exploited maliciously.

• SEC Form 8-Ks (DarCache 8-K): Provides relevant SEC filings. These filings often contain disclosures about security incidents, which can provide additional context for attribution.

Complementary Solutions

While ThreatNG is a powerful standalone solution for external attack surface management, its data can be incredibly valuable when combined with other cybersecurity solutions, enhancing attribution capabilities:

• Security Information and Event Management (SIEM) / Security Orchestration, Automation, and Response (SOAR) Platforms: ThreatNG's continuous monitoring and external assessment findings can feed directly into a SIEM, enriching log data with external context. For instance, if ThreatNG identifies a new exposed sensitive port or a critical vulnerability (e.g., from DarCache KEV), this information can trigger alerts in the SIEM. If an attack then leverages this specific exposure, the SIEM's internal logs (e.g., firewall logs, endpoint detection) combined with ThreatNG's external insights would provide a much clearer picture of the attack path, aiding attribution. SOAR platforms could then automate responses based on these combined insights. For example, if ThreatNG identifies compromised credentials on the dark web for a key executive, a SOAR playbook could automatically trigger password resets and MFA enforcement, while also feeding this information into an attribution report.

• Endpoint Detection and Response (EDR) / Extended Detection and Response (XDR) Solutions: EDR/XDR tools focus on internal network and endpoint activity. When ThreatNG identifies an external vulnerability, such as a susceptible web application or exposed sensitive code, and an EDR detects malicious activity originating from that vector, the combined data provides a strong link between the external exposure and internal compromise. This synergy can help attribute the internal activity to an external attack vector identified by ThreatNG, potentially linking it to specific attacker TTPs observed by both solutions. For instance, if ThreatNG identifies a critical vulnerability in a web server and the EDR detects a particular variant of malware originating from that server, this correlation strengthens the attribution to an attacker known to use that malware and exploit.

• Threat Intelligence Platforms (TIPs): While ThreatNG has its robust intelligence repositories (DarCache), integrating its findings with a broader TIP can provide even richer context. For example, ThreatNG might identify a specific IP address associated with an attack. A TIP could then provide additional context on that IP, such as its historical malicious activities, associations with known threat groups, or shared infrastructure, thereby enhancing the attribution process by connecting ThreatNG's observations to a broader network of adversary intelligence.

• Digital Forensics and Incident Response (DFIR) Tools: ThreatNG's detailed external assessments, particularly in terms of data leak susceptibility, sensitive code exposure, and dark web presence, provide critical starting points for DFIR investigations. If a breach occurs, the DFIR team can utilize ThreatNG's findings to rapidly identify the likely initial access vectors or exfiltration points, thereby accelerating their analysis and enabling quicker attribution by focusing on relevant evidence. For instance, if ThreatNG detected an open S3 bucket and a data leak occurred, DFIR teams would prioritize investigating that specific cloud storage.

By working with these complementary solutions, ThreatNG's external perspective significantly enhances the overall ability to attribute cyberattacks by providing the crucial "outside-in" view that bridges the gap between external vulnerabilities and internal malicious activity.