#Fact Check: Old Photo Misused to Claim Israeli Helicopter Downed in Lebanon!

Introduction

The Telecom Regulatory Authority of India (TRAI) has directed all telcos to set up detection systems based on Artificial Intelligence and Machine Learning (AI/ML) technologies in order to identify and control spam calls and text messages from unregistered telemarketers (UTMs).

The TRAI Directed telcos

The telecom regulator, TRAI, has directed all Access Providers to detect Unsolicited commercial communication (UCC)by systems, which is based on Artificial Intelligence and Machine Learning to detect, identify, and act against senders of Commercial Communication who are not registered in accordance with the provisions of the Telecom Commercial Communication Customer Preference Regulations, 2018 (TCCCPR-2018). Unregistered Telemarketers (UTMs) are entities that do not register with Access Providers and use 10-digit mobile numbers to send commercial communications via SMS or calls.

TRAI steps to curb Unsolicited commercial communication

TRAI has taken several initiatives to reduce Unsolicited Commercial Communication (UCC), which is a major source of annoyance for the public. It has resulted in fewer complaints filed against Registered Telemarketers (RTMs). Despite the TSPs’ efforts, UCC from Unregistered Telemarketers (UTMs) continues. Sometimes, these UTMs use messages with bogus URLs and phone numbers to trick clients into revealing crucial information, leading to financial loss.

To detect, identify, and prosecute all Unregistered Telemarketers (UTMs), the TRAI has mandated that Access Service Providers implement the UCC.

Detect the System with the necessary functionalities within the TRAI’s Telecom Commercial Communication Customer Preference Regulations, 2018 framework.

Access service providers have implemented such detection systems based on their applicability and practicality. However, because UTMs are constantly creating new strategies for sending unwanted communications, the present UCC detection systems provided by Access Service providers cannot detect such UCC.

TRAI also Directs Telecom Providers to Set Up Digital Platform for Customer Consent to Curb Promotional Calls and Messages.

Unregistered Telemarketers (UTMs) sometimes use messages with fake URLs and phone numbers to trick customers into revealing essential information, resulting in financial loss.

TRAI has urged businesses like banks, insurance companies, financial institutions, and others to re-verify their SMS content templates with telcos within two weeks. It also directed telecom companies to stop misusing commercial messaging templates within the next 45 days.

The telecom regulator has also instructed operators to limit the number of variables in a content template to three. However, if any business intends to utilise more than three variables in a content template for communicating with their users, this should be permitted only after examining the example message, as well as adequate justifications and justification.

In order to ensure consistency in UCC Detect System implementations, TRAI has directed all Access Providers to deploy UCC and detect systems based on artificial intelligence and Machine Learning that are capable of constantly evolving to deal with new signatures, patterns, and techniques used by UTMs.

Access Providers have also been directed to use the DLT platform to share intelligence with others. Access Providers have also been asked to ensure that such UCC Detect System detects senders that send unsolicited commercial communications in bulk and do not comply with the requirements. All Access Providers are directed to follow the instructions and provide an update on actions done within thirty days.

The move by TRAI is to curb the menacing calls as due to this, the number of scam cases is increasing, and now a new trend of scams started as recently, a Twitter user reported receiving an automated call from +91 96681 9555 with the message “This call is from Delhi Police.” It then asked her to stay in the queue since some of her documents needed to be picked up. Then he said he works as a sub-inspector at the Kirti Nagar police station in New Delhi. He then inquired whether she had recently misplaced her Aadhaar card, PAN card, or ATM card, to which she replied ‘no’. The scammer then poses as a cop and requests that she authenticate the last four digits of her card because they have found a card with her name on it. And a lot of other people tweeted about it.

Conclusion

TRAI directed the telcos to check the calls and messages from Unregistered numbers. This step of TRAI will curb the pesky calls and messages and catch the Frauds who are not registered with the regulation. Sometimes the unregistered sender sends fraudulent links, and through these fraudulent calls and messages, the sender tries to take the personal information of the customers, which results in financial losses.

Introduction 

In today's digital age, we consume a lot of information and content on social media apps, and it has become a daily part of our lives. Additionally, the algorithm of these apps is such that once you like a particular category of content or show interest in it, the algorithm starts showing you a lot of similar content. With this, the hype around becoming a content creator has also increased, and people have started making short reel videos and sharing a lot of information. There are influencers in every field, whether it's lifestyle, fitness, education, entertainment, vlogging, and now even legal advice.

The online content, reels, and viral videos by social media influencers giving legal advice can have far-reaching consequences. ‘LAW’ is a vast subject where even a single punctuation mark holds significant meaning. If it is misinterpreted or only partially explained in social media reels and short videos, it can lead to serious consequences. Laws apply based on the facts and circumstances of each case, and they can differ depending on the nature of the case or offence. This trend of ‘swipe for legal advice’ or ‘law in 30 seconds’, along with the rise of the increasing number of legal influencers, poses a serious problem in the online information landscape. It raises questions about the credibility and accuracy of such legal advice, as misinformation can mislead the masses, fuel legal confusion, and create risks.

Bar Council of India’s stance against legal misinformation on social media platforms 

The Bar Council of India (BCI) on Monday (March 17, 2025) expressed concern over the rise of self-styled legal influencers on social media, stating that many without proper credentials spread misinformation on critical legal issues. Additionally, “Incorrect or misleading interpretations of landmark judgments like the Citizenship Amendment Act (CAA), the Right to Privacy ruling in Justice K.S. Puttaswamy (Retd.) v. Union of India, and GST regulations have resulted in widespread confusion, misguided legal decisions, and undue judicial burden,” the body said. The BCI also ordered the mandatory cessation of misleading and unauthorised legal advice dissemination by non-enrolled individuals and called for the establishment of stringent vetting mechanisms for legal content on digital platforms. The BCI emphasised the need for swift removal of misleading legal information.

Conclusion

Legal misinformation on social media is a growing issue that not only disrupts public perception but also influences real-life decisions. The internet is turning complex legal discourse into a chaotic game of whispers, with influencers sometimes misquoting laws and self-proclaimed "legal experts" offering advice that wouldn't survive in a courtroom. The solution is not censorship, but counterbalance. Verified legal voices need to step up, fact-checking must be relentless, and digital literacy must evolve to keep up with the fast-moving world of misinformation. Otherwise, "legal truth" could be determined by whoever has the best engagement rate, rather than by legislation or precedent.

References:

• https://www.thehindu.com/news/national/bci-warns-against-legal-misinformation-bans-influencer-promotions/article69340049.ece

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Executive Summary:

BrazenBamboo’s DEEPDATA malware represents a new wave of advanced cyber espionage tools, exploiting a zero-day vulnerability in Fortinet FortiClient to extract VPN credentials and sensitive data through fileless malware techniques and secure C2 communications. With its modular design, DEEPDATA targets browsers, messaging apps, and password stores, while leveraging reflective DLL injection and encrypted DNS to evade detection. Cross-platform compatibility with tools like DEEPPOST and LightSpy highlights a coordinated development effort, enhancing its espionage capabilities. To mitigate such threats, organizations must enforce network segmentation, deploy advanced monitoring tools, patch vulnerabilities promptly, and implement robust endpoint protection. Vendors are urged to adopt security-by-design practices and incentivize vulnerability reporting, as vigilance and proactive planning are critical to combating this sophisticated threat landscape.

Introduction

The increased use of zero-day vulnerabilities by more complex threat actors reinforces the importance of more developed countermeasures. One of the threat actors identified is BrazenBamboo uses a zero-day vulnerability in Fortinet FortiClient for Windows through the DEEPDATA advanced malware framework. This research explores technical details about DEEPDATA, the tricks used in its operations, and its other effects.

Technical Findings

1. Vulnerability Exploitation Mechanism

The vulnerability in Fortinet’s FortiClient lies in its failure to securely handle sensitive information in memory. DEEPDATA capitalises on this flaw via a specialised plugin, which:

• Accesses the VPN client’s process memory.
• Extracts unencrypted VPN credentials from memory, bypassing typical security protections.
• Transfers credentials to a remote C2 server via encrypted communication channels.

2. Modular Architecture

DEEPDATA exhibits a highly modular design, with its core components comprising:

• Loader Module (data.dll): Decrypts and executes other payloads.
• Orchestrator Module (frame.dll): Manages the execution of multiple plugins.
• FortiClient Plugin: Specifically designed to target Fortinet’s VPN client.

Each plugin operates independently, allowing flexibility in attack strategies depending on the target system.

3. Command-and-Control (C2) Communication

DEEPDATA establishes secure channels to its C2 infrastructure using WebSocket and HTTPS protocols, enabling stealthy exfiltration of harvested data. Technical analysis of network traffic revealed:

• Dynamic IP switching for C2 servers to evade detection.
• Use of Domain Fronting, hiding C2 communication within legitimate HTTPS traffic.
• Time-based communication intervals to minimise anomalies in network behavior.

4. Advanced Credential Harvesting Techniques

Beyond VPN credentials, DEEPDATA is capable of:

• Dumping password stores from popular browsers, such as Chrome, Firefox, and Edge.
• Extracting application-level credentials from messaging apps like WhatsApp, Telegram, and Skype.
• Intercepting credentials stored in local databases used by apps like KeePass and Microsoft Outlook.

5. Persistence Mechanisms

To maintain long-term access, DEEPDATA employs sophisticated persistence techniques:

• Registry-based persistence: Modifies Windows registry keys to reload itself upon system reboot.
• DLL Hijacking: Substitutes legitimate DLLs with malicious ones to execute during normal application operations.
• Scheduled Tasks and Services: Configures scheduled tasks to periodically execute the malware, ensuring continuous operation even if detected and partially removed.

Additional Tools in BrazenBamboo’s Arsenal

1. DEEPPOST

A complementary tool used for data exfiltration, DEEPPOST facilitates the transfer of sensitive files, including system logs, captured credentials, and recorded user activities, to remote endpoints.

2. LightSpy Variants

• The Windows variant includes a lightweight installer that downloads orchestrators and plugins, expanding espionage capabilities across platforms.
• Shellcode-based execution ensures that LightSpy’s payload operates entirely in memory, minimising artifacts on the disk.

3. Cross-Platform Overlaps

BrazenBamboo’s shared codebase across DEEPDATA, DEEPPOST, and LightSpy points to a centralised development effort, possibly linked to a Digital Quartermaster framework. This shared ecosystem enhances their ability to operate efficiently across macOS, iOS, and Windows systems.

Notable Attack Techniques

1. Memory Injection and Data Extraction

Using Reflective DLL Injection, DEEPDATA injects itself into legitimate processes, avoiding detection by traditional antivirus solutions.

• Memory Scraping: Captures credentials and sensitive information in real-time.
• Volatile Data Extraction: Extracts transient data that only exists in memory during specific application states.

2. Fileless Malware Techniques

DEEPDATA leverages fileless infection methods, where its payload operates exclusively in memory, leaving minimal traces on the system. This complicates post-incident forensic investigations.

3. Network Layer Evasion

By utilising encrypted DNS queries and certificate pinning, DEEPDATA ensures that network-level defenses like intrusion detection systems (IDS) and firewalls are ineffective in blocking its communications.

Recommendations

1. For Organisations

• Apply Network Segmentation: Isolate VPN servers from critical assets.
• Enhance Monitoring Tools: Deploy behavioral analysis tools that detect anomalous processes and memory scraping activities.
• Regularly Update and Patch Software: Although Fortinet has yet to patch this vulnerability, organisations must remain vigilant and apply fixes as soon as they are released.

2. For Security Teams

• Harden Endpoint Protections: Implement tools like Memory Integrity Protection to prevent unauthorised memory access.
• Use Network Sandboxing: Monitor and analyse outgoing network traffic for unusual behaviors.
• Threat Hunting: Proactively search for indicators of compromise (IOCs) such as unauthorised DLLs (data.dll, frame.dll) or C2 communications over non-standard intervals.

3. For Vendors

• Implement Security by Design: Adopt advanced memory protection mechanisms to prevent credential leakage.
• Bug Bounty Programs: Encourage researchers to report vulnerabilities, accelerating patch development.

Conclusion

DEEPDATA is a form of cyber espionage and represents the next generation of tools that are more advanced and tunned for stealth, modularity and persistence. While Brazen Bamboo is in the process of fine-tuning its strategies, the organisations and vendors have to be more careful and be ready to respond to these tricks. The continuous updating, the ability to detect the threats and a proper plan on how to deal with incidents are crucial in combating the attacks.

References:

1. https://thehackernews.com/2024/11/warning-deepdata-malware-exploiting.html‍
2. http://www.theregister.com/2024/11/19/china_brazenbamboo_fortinet_0day/