Executive Summary

On January 3, 2026, a threat group calling itself Scattered Lapsus$ Hunters (SLH), with alleged ties to ShinyHunters and Lapsus$, claimed to have successfully breached the cybersecurity firm Resecurity. The group posted screenshots on Telegram as proof, alleging access to internal chats, employee data, and client intelligence. In a swift and public rebuttal, Resecurity denied any compromise of its production systems. The firm stated that the attackers were, in fact, lured into and contained within a pre-existing, high-interaction honeypot. According to Resecurity, all data and systems the attackers accessed were synthetic and part of a cyber deception environment designed to study their methods. The incident highlights the growing use of deception technology as a proactive defense and intelligence gathering tool.

Threat Overview

The incident involves a public clash between a threat actor group and a cybersecurity vendor. The group, Scattered Lapsus$ Hunters, attempted to gain notoriety by claiming a high-profile victim. Their TTPs appear to align with groups like Lapsus$, focusing on credential theft, social engineering, and data exfiltration for public shaming or extortion. The group claimed the attack was in retaliation for Resecurity allegedly attempting to socially engineer them, suggesting a tit-for-tat engagement.

Resecurity's defense was not passive; it was an active, offensive defense strategy. By their account, they successfully turned the attackers' efforts into a live intelligence-gathering exercise. They leveraged a honeypot—a decoy computer system intended to trap and analyze attackers—to observe the group's tools, techniques, and procedures in a safe, isolated environment. The firm had even published a blog post on December 24, 2025, detailing their use of synthetic data in cyber deception, lending credibility to their claims.

Technical Analysis

Based on Resecurity's account, the attack unfolded within their deception environment.

1. Engagement (T1566 - Phishing): The initial vector used by SLH to access the honeypot is not detailed, but it was likely through credentials planted for discovery or a simulated vulnerable application.
2. Discovery (T1083 - File and Directory Discovery): Once inside the decoy environment (which may have included a simulated Mattermost chat server), the attackers began exploring, looking for valuable data.
3. Collection (T1005 - Data from Local System): The attackers collected what they believed to be sensitive data: internal chats, employee lists, and client reports. However, all this data was synthetic, created by Resecurity for this purpose.
4. Exfiltration (T1041 - Exfiltration Over C2 Channel): The attackers exfiltrated the fake data to their own systems.
5. Impact (TA0040 - Impact): The attackers attempted to cause reputational damage by posting their 'findings' on Telegram. This backfired when Resecurity publicly revealed the deception. The SLH group later removed their post.

This incident serves as a masterclass in leveraging M1056 - Pre-compromise mitigations, specifically using decoy environments. The goal of a honeypot is not just to be a tar pit but to provide high-fidelity telemetry on attacker behavior that can be used to strengthen real defenses.

Impact Assessment

• For Scattered Lapsus$ Hunters: The impact is severely negative. Their attempt at a high-profile victory resulted in public humiliation, loss of credibility within the underground community, and the exposure of their TTPs to a security vendor.
• For Resecurity: The impact is overwhelmingly positive. They successfully defended their network, demonstrated the effectiveness of their cyber deception technology, gathered valuable threat intelligence, and turned a potential PR crisis into a marketing victory. This validates their security posture and expertise.
• For the Industry: This case provides a powerful example of active defense. It may encourage wider adoption of deception technologies as a viable strategy for high-value targets to move beyond purely passive, preventative security controls.

Cyber Observables for Detection

• Traffic directed towards known honeypot infrastructure.
• Use of credentials that only exist within a decoy environment.
• Interaction with files or services that are tagged as honey-tokens (e.g., fake AWS keys, decoy documents).

Detection & Response

• Honeypot Deployment: Strategically deploy various types of honeypots (low, medium, and high-interaction) across the network. High-interaction honeypots, like the one Resecurity likely used, provide the most valuable intelligence.
• Honey-Tokens: Seed production systems with honey-tokens—decoy data like fake API keys, database records, or user accounts. Any interaction with these tokens is a high-fidelity indicator of a breach. This is a core part of D3-DO: Decoy Object.
• Alert Triage: SOC analysts must be trained to recognize and prioritize alerts originating from deception platforms. An alert from a honeypot is a confirmed indicator of malicious activity and should be treated with the highest urgency.

Mitigation

• Cyber Deception Platform: Implement a comprehensive cyber deception platform. These platforms automate the creation, deployment, and management of honeypots and honey-tokens, making the strategy scalable. This is the practical application of D3-DE: Decoy Environment.
• Intelligence Integration: Feed the intelligence gathered from honeypots back into the security program. The TTPs, tools, and IP addresses observed can be used to create new detection rules for SIEM and EDR, update firewall blocklists, and inform threat hunting exercises.
• Public Relations Strategy: Have a pre-planned communications strategy for when a deception-based defense is successful. As Resecurity demonstrated, controlling the narrative and quickly refuting false claims is key to turning the tables on the attacker.