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Cybersecurity experts are raising red flags as sophisticated cyber attacks target the Indian government using a trio of newly discovered backdoors. These malware campaigns—named SHEETCREEP, FIREPOWER, and MAILCREEP—exploit widely used platforms like Google Sheets, Firebase, and Microsoft Graph API, allowing attackers to stealthily command and control infected systems. The campaigns are suspected to be orchestrated by Pakistan-backed APT36, a threat actor known for targeting South Asian institutions. The attackers’ arsenal reportedly includes AI-crafted malware, highlighting an alarming evolution in the sophistication and automation of state-linked cyber operations.
New Backdoors Exploit Everyday Platforms
The first of these threats, SHEETCREEP, leverages Google Sheets as a covert command and control (C2) channel. By embedding instructions into seemingly harmless spreadsheets, attackers can manipulate targeted systems without raising traditional red flags. FIREPOWER, meanwhile, exploits Firebase, Google’s app development platform, to maintain persistence and receive commands. MAILCREEP targets Microsoft Graph API, giving the attackers the ability to interact with emails, calendars, and other Microsoft 365 resources to exfiltrate sensitive data or deploy additional malware.
AI-Powered Malware: A Growing Concern
Zscaler ThreatLabz reports indicate that the malware in these campaigns may be AI-enhanced, allowing it to adapt dynamically to security defenses and evade detection. This level of automation marks a dangerous shift in the capabilities of APT36, traditionally known for conventional phishing and malware attacks.
Targeting Indian Government Agencies
Indian government departments have become high-priority targets, with attackers focusing on sensitive information stored across cloud services. The exploitation of productivity platforms like Google Sheets and Microsoft Graph demonstrates a move away from traditional attack vectors, favoring platforms integrated deeply into daily workflows, making detection more difficult.
The Threat Actor Behind the Campaign
APT36, sometimes called Mythic Leopard, has a long history of cyber espionage in South Asia. Analysts suspect that the group benefits from state backing, enabling them to invest in AI-enhanced malware development. Past campaigns have targeted government entities, defense contractors, and critical infrastructure.
Operational Tactics and Techniques
The use of cloud services as C2 infrastructure demonstrates an evolving tactic in modern APT campaigns. By abusing platforms like Firebase and Microsoft Graph API, attackers avoid using easily detectable malicious servers, instead hiding in plain sight. The AI-driven adaptability allows malware to respond to endpoint defenses in real-time, significantly increasing its chance of successful infiltration.
Global Implications of APT36 Activities
While the immediate impact is focused on Indian government networks, these attack techniques have global relevance. Any organization relying heavily on cloud productivity platforms could be vulnerable. Security experts warn that the automation and AI integration observed in these attacks are likely to become a standard component of state-backed cyber espionage campaigns worldwide.
Escalation of AI-Enhanced Threats
The sophistication of these attacks underscores a worrying trend: AI-driven malware is no longer theoretical. With backdoors like SHEETCREEP, FIREPOWER, and MAILCREEP, attackers can execute highly targeted operations with minimal human intervention, evading traditional signature-based detection tools. This development emphasizes the urgent need for adaptive, AI-aware cybersecurity defenses.
What Undercode Says:
Rising Threats in Everyday Tools
The targeting of widely used productivity platforms like Google Sheets, Firebase, and Microsoft Graph API signals a shift in attacker strategy from infrastructure-heavy attacks to more covert, workflow-centric operations. Organizations must reassess the security posture of even the most mundane cloud tools, as these are now prime attack vectors.
AI Integration Raises the Stakes
AI-driven malware significantly amplifies risk. Unlike traditional malware, it can modify its behavior based on the environment, automatically bypassing endpoint detection and minimizing operational footprints. This trend demands a reevaluation of endpoint and cloud security protocols.
Strategic Implications for India
APT36’s focus on Indian government agencies is both a geopolitical and cybersecurity concern. These attacks not only threaten sensitive national data but also underscore the importance of regional cyber defense collaborations. Policies must evolve to counter AI-augmented APT attacks effectively.
Broader Global Cybersecurity Lessons
The adoption of cloud-based C2 infrastructure suggests that future cyber operations will increasingly exploit legitimate services, complicating threat detection worldwide. Companies beyond government institutions must recognize the risk and implement layered defenses combining AI-driven threat detection and user behavior monitoring.
Policy and Defense Recommendations
Continuous monitoring of cloud activity logs for anomalies.
Implementation of AI-based detection and automated incident response.
Mandatory cybersecurity hygiene training for employees handling cloud-based tools.
Cross-border intelligence-sharing to preempt state-backed cyber campaigns.
🔍 Fact Checker Results:
✅ SHEETCREEP, FIREPOWER, and MAILCREEP are verified new backdoors targeting Indian government systems.
✅ The campaign is linked to APT36, known for South Asian cyber espionage.
❌ No confirmed evidence that all malware is entirely AI-driven; AI assistance in code generation is suspected but not fully confirmed.
📊 Prediction:
APT36 and similar threat actors are likely to escalate AI-integrated campaigns targeting cloud services globally. Organizations reliant on Google Workspace, Firebase, and Microsoft 365 should expect an uptick in targeted attacks, with AI-driven malware becoming increasingly autonomous, adaptive, and difficult to detect. Cyber defenses will need to evolve toward AI-assisted monitoring and anomaly detection to stay ahead of these next-generation threats.
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References:
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