#FactCheck - Debunking Manipulated Photos of Smiling Secret Service Agents During Trump Assassination Attempt

Executive Summary:

New Linux malware has been discovered by a cybersecurity firm Volexity, and this new strain of malware is being referred to as DISGOMOJI. A Pakistan-based threat actor alias ‘UTA0137’ has been identified as having espionage aims, with its primary focus on Indian government entities.  Like other common forms of backdoors and botnets involved in different types of cyberattacks, DISGOMOJI, the malware  allows the use of commands to capture screenshots, search for files to steal, spread additional payloads, and transfer files. DISGOMOJI  uses Discord (messaging service)  for Command & Control (C2)  and uses emojis  for C2 communication. This malware targets Linux operating systems.

The DISCOMOJI Malware:  

• The DISGOMOJI malware opens a specific channel in a Discord server and every new channel corresponds to a new victim. This means that the attacker can communicate with the victim one at a time.

• This particular malware connects with the attacker-controlled Discord server using Emoji, a form of relay protocol. The attacker provides unique emojis as instructions, and the malware uses emojis as a feedback to the subsequent command status.

• For instance, the ‘camera with flash’ emoji is used to screenshots the device of the victim or to steal, the ‘fox’ emoji cracks all Firefox profiles, and the ‘skull’ emoji kills the malware process.

• This C2 communication is done using emojis to ensure messaging between infected contacts, and it is almost impossible for Discord to shut down the malware as it can always change the account details of Discord it is using once the maliciou server is blocked.

• The malware also has capabilities aside from the emoji-based C2 such as network probing, tunneling, and data theft that are needed to help the UTA0137 threat actor in achieving its espionage goals.

Specific emojis used for different commands by UTA0137:

• Camera with Flash (📸): Captures a picture of the target device’s screen as per the victim’s directions.

• Backhand Index Pointing Down (👇): Extracts files from the targeted device and sends them to the command channel in the form of attachments.

• Backhand Index Pointing Right (👉): This process involves sending a file found on the victim’s device to another web-hosted file storage service known as Oshi or oshi[. ]at.

• Backhand Index Pointing Left (👈): Sends a file from the victim’s device to transfer[. ]sh, which is an online service for sharing files on the Internet.

• Fire (🔥): Finds and transmits all files with certain extensions that exist on the victim’s device, such as *. txt, *. doc, *. xls, *. pdf, *. ppt, *. rtf, *. log, *. cfg, *. dat, *. db, *. mdb, *. odb, *. sql, *. json, *. xml, *. php, *. asp, *. pl, *. sh, *. py, *. ino, *. cpp, *. java,

• Fox (🦊): This works by compressing all Firefox related profiles in the affected device. 

• Skull (💀): Kills the malware process in windows using ‘os. Exit()’

• Man Running (🏃‍♂️):  Execute a command on a victim’s device. This command receives an argument, which is the command to execute.

• Index Pointing up (👆) : Upload a file to the victim's device. The file to upload is attached along with this emoji

Analysis:   

The analysis was carried out for one of the indicator of compromised SHA-256 hash file-  C981aa1f05adf030bacffc0e279cf9dc93cef877f7bce33ee27e9296363cf002.

It is found that most of the vendors have marked the file as trojan in virustotal and the graph explains the malicious nature of the contacted domains and IPs.

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Discord & C2 Communication  for UTA0137:

• Stealthiness: Discord is a well-known messaging platform used for different purposes, which means that sending any messages or files on the server should not attract suspicion. Such stealthiness makes it possible for UTA0137 to remain dormant for greater periods before launching an attack.

• Customization: UTA0137 connected to Discord is able to create specific channels for distinct victims on the server. Such a framework allows the attackers to communicate with each of the victims individually to make a process more accurate and efficient.

• Emoji-based protocol: For C2 communication, emojis really complicates the attempt that Discord might make to interfere with the operations of the malware. In case the malicious server gets banned, malware could easily be recovered, especially by using the Discord credentials from the C2 server.

• Persistence: The malware, as stated above, has the ability to perpetually exist to hack the system and withstand rebooting of systems so that the virus can continue to operate without being detected by the owner of the hacked system.

• Advanced capabilities: Other features of DISGOMOJI are the Network Map using Nmap scanner, network tunneling through Chisel and Ligolo and Data Exfiltration by File Sharing services. These capabilities thus help in aiding the espionage goals of UTA0137.

• Social engineering: The virus and the trojan can show the pop-up windows and prompt messages, for example the fake update for firefox and similar applications, where the user can be tricked into inputting the password.

• Dynamic credential fetching: The malware does not write the hardcoded values of the credentials in order to connect it to the discord server. This also inconveniences analysts as they are unable to easily locate the position of the C2 server.

• Bogus informational and error messages: They never show any real information or errors because they do not want one to decipher the malicious behavior easily.

Recommendations to mitigate the risk of UTA0137:

• Regularly Update Software and Firmware: It is essential to regularly update all the application software and firmware of different devices, particularly, routers, to prevent hackers from exploiting the discovered and disclosed flaws. This includes fixing bugs such as CVE-2024-3080 and CVE-2024-3912 on ASUS routers, which basically entails solving a set of problems.

• Implement Multi-Factor Authentication: There are statistics that show how often user accounts are attacked, it is important to incorporate multi-factor authentication to further secure the accounts.

• Deploy Advanced Malware Protection: Provide robust guard that will help the user recognize and prevent the execution of the DISGOMOJI malware and similar threats.

• Enhance Network Segmentation: Utilize stringent network isolation mechanisms that seek to compartmentalize the key systems and data from the rest of the network in order to minimize the attack exposure.

• Monitor Network Activity: Scanning Network hour to hour for identifying and handling the security breach and the tools such as Nmap, Chisel, Ligolo etc can be used.

• Utilize Threat Intelligence: To leverage advanced threats intelligence which will help you acquire knowledge on previous threats and vulnerabilities and take informed actions.

• Secure Communication Channels: Mitigate the problem of the leakage of developers’ credentials and ways of engaging with the discord through loss of contact to prevent abusing attacks or gaining control over Discord as an attack vector.

• Enforce Access Control: Regularly review and update the user authentication processes by adopting stricter access control measures that will allow only the right personnel to access the right systems and information.

• Conduct Regular Security Audits: It is important to engage in security audits periodically in an effort to check some of the weaknesses present within the network or systems.

• Implement Incident Response Plan: Conduct a risk assessment, based on that design and establish an efficient incident response kit that helps in the early identification, isolation, and management of security breaches.

• Educate Users: Educate users on cybersecurity hygiene, opportunities to strengthen affinity with the University, and conduct retraining on threats like phishing and social engineering.

Conclusion:

The new threat actor named UTA0137 from Pakistan who was utilizing DISGOMOJI malware to attack Indian government institutions using embedded emojis with a command line through the Discord app was discovered by Volexity. It has the capability to exfiltrate and aims to steal the data of government entities. The UTA0137 was continuously improved over time to permanently communicate with victims. It underlines the necessity of having strong protection from viruses and hacker attacks, using secure passwords and unique codes every time, updating the software more often and having high-level anti-malware tools. Organizations can minimize advanced threats, the likes of DISGOMOJI and protect sensitive data by improving network segmentation, continuous monitoring of activities, and users’ awareness.

References:

https://otx.alienvault.com/pulse/66712446e23b1d14e4f293eb

https://thehackernews.com/2024/06/pakistani-hackers-use-disgomoji-malware.html?m=1

https://cybernews.com/news/hackers-using-emojis-to-command-malware/

https://www.blackhatethicalhacking.com/news/disgomoji-new-linux-malware-uses-emojis-for-command-execution/

https://www.volexity.com/blog/2024/06/13/disgomoji-malware-used-to-target-indian-government/

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Executive Summary:

In late 2024 an Indian healthcare provider experienced a severe cybersecurity attack that demonstrated how powerful AI ransomware is. This blog discusses the background to the attack, how it took place and the effects it caused (both medical and financial), how organisations reacted, and the final result of it all, stressing on possible dangers in the healthcare industry with a lack of sufficiently adequate cybersecurity measures in place. The incident also interrupted the normal functioning of business and explained the possible economic and image losses from cyber threats. Other technical results of the study also provide more evidence and analysis of the advanced AI malware and best practices for defending against them. 

1. Introduction

The integration of artificial intelligence (AI) in cybersecurity has revolutionised both defence mechanisms and the strategies employed by cybercriminals. AI-powered attacks, particularly ransomware, have become increasingly sophisticated, posing significant threats to various sectors, including healthcare. This report delves into a case study of an AI-powered ransomware attack on a prominent Indian healthcare provider in 2024, analysing the attack's execution, impact, and the subsequent response, along with key technical findings.

2. Background 

 In late 2024, a leading healthcare organisation in India which is involved in the research and development of AI techniques fell prey to a ransomware attack that was AI driven to get the most out of it. With many businesses today relying on data especially in the healthcare industry that requires real-time operations, health care has become the favourite of cyber criminals. AI aided attackers were able to cause far more detailed and damaging attack that severely affected the operation of the provider whilst jeopardising the safety of the patient information.  

 3. Attack Execution 

The attack began with the launch of a phishing email designed to target a hospital administrator. They received an email with an infected attachment which when clicked in some cases injected the AI enabled ransomware into the hospitals network. AI incorporated ransomware was not as blasé as traditional ransomware, which sends copies to anyone, this studied the hospital’s IT network. First, it focused and targeted important systems which involved implementation of encryption such as the electronic health records and the billing departments. 

The fact that the malware had an AI feature allowed it to learn and adjust its way of propagation in the network, and prioritise the encryption of most valuable data. This accuracy did not only increase the possibility of the potential ransom demand but also it allowed reducing the risks of the possibility of early discovery. 

 4. Impact 

•  The consequences of the attack were immediate and severe: The consequences of the attack were immediate and severe.
•  Operational Disruption: The centralization of important systems made the hospital cease its functionality through the acts of encrypting the respective components. Operations such as surgeries, routine medical procedures and admitting of patients were slowed or in some cases referred to other hospitals. 
•  Data Security: Electronic patient records and associated billing data became off-limit because of the vulnerability of patient confidentiality. The danger of data loss was on the verge of becoming permanent, much to the concern of both the healthcare provider and its patients. 
•  Financial Loss: The attackers asked for 100 crore Indian rupees (approximately 12 USD million) for the decryption key. Despite the hospital not paying for it, there were certain losses that include the operational loss due to the server being down, loss incurred by the patients who were affected in one way or the other, loss incurred in responding to such an incident and the loss due to bad reputation. 

5. Response

As soon as the hotel’s management was informed about the presence of ransomware, its IT department joined forces with cybersecurity professionals and local police. The team decided not to pay the ransom and instead recover the systems from backup. Despite the fact that this was an ethically and strategically correct decision, it was not without some challenges. Reconstruction was gradual, and certain elements of the patients’ records were permanently erased. 

 In order to avoid such attacks in the future, the healthcare provider put into force several organisational and technical actions such as network isolation and increase of cybersecurity measures. Even so, the attack revealed serious breaches in the provider’s IT systems security measures and protocols. 

6. Outcome

The attack had far-reaching consequences:

• Financial Impact: A healthcare provider suffers a lot of crashes in its reckoning due to substantial service disruption as well as bolstering cybersecurity and compensating patients. 
•  Reputational Damage: The leakage of the data had a potential of causing a complete loss of confidence from patients and the public this affecting the reputation of the provider. This, of course, had an effect on patient care, and ultimately resulted in long-term effects on revenue as patients were retained. 
•  Industry Awareness: The breakthrough fed discussions across the country on how to improve cybersecurity provisions in the healthcare industry. It woke up the other care providers to review and improve their cyber defence status. 

7. Technical Findings

The AI-powered ransomware attack on the healthcare provider revealed several technical vulnerabilities and provided insights into the sophisticated mechanisms employed by the attackers. These findings highlight the evolving threat landscape and the importance of advanced cybersecurity measures.

7.1 Phishing Vector and Initial Penetration

• Sophisticated Phishing Tactics: The phishing email was crafted with precision, utilising AI to mimic the communication style of trusted contacts within the organisation. The email bypassed standard email filters, indicating a high level of customization and adaptation, likely due to AI-driven analysis of previous successful phishing attempts.
• Exploitation of Human Error: The phishing email targeted an administrative user with access to critical systems, exploiting the lack of stringent access controls and user awareness. The successful penetration into the network highlighted the need for multi-factor authentication (MFA) and continuous training on identifying phishing attempts.

7.2 AI-Driven Malware Behavior

• Dynamic Network Mapping: Once inside the network, the AI-powered malware executed a sophisticated mapping of the hospital's IT infrastructure. Using machine learning algorithms, the malware identified the most critical systems—such as Electronic Health Records (EHR) and the billing system—prioritising them for encryption. This dynamic mapping capability allowed the malware to maximise damage while minimising its footprint, delaying detection.
• Adaptive Encryption Techniques: The malware employed adaptive encryption techniques, adjusting its encryption strategy based on the system's response. For instance, if it detected attempts to isolate the network or initiate backup protocols, it accelerated the encryption process or targeted backup systems directly, demonstrating an ability to anticipate and counteract defensive measures.
• Evasive Tactics: The ransomware utilised advanced evasion tactics, such as polymorphic code and anti-forensic features, to avoid detection by traditional antivirus software and security monitoring tools. The AI component allowed the malware to alter its code and behaviour in real time, making signature-based detection methods ineffective.

7.3 Vulnerability Exploitation

• Weaknesses in Network Segmentation: The hospital’s network was insufficiently segmented, allowing the ransomware to spread rapidly across various departments. The malware exploited this lack of segmentation to access critical systems that should have been isolated from each other, indicating the need for stronger network architecture and micro-segmentation.
• Inadequate Patch Management: The attackers exploited unpatched vulnerabilities in the hospital’s IT infrastructure, particularly within outdated software used for managing patient records and billing. The failure to apply timely patches allowed the ransomware to penetrate and escalate privileges within the network, underlining the importance of rigorous patch management policies.

7.4 Data Recovery and Backup Failures

• Inaccessible Backups: The malware specifically targeted backup servers, encrypting them alongside primary systems. This revealed weaknesses in the backup strategy, including the lack of offline or immutable backups that could have been used for recovery. The healthcare provider’s reliance on connected backups left them vulnerable to such targeted attacks.
• Slow Recovery Process: The restoration of systems from backups was hindered by the sheer volume of encrypted data and the complexity of the hospital’s IT environment. The investigation found that the backups were not regularly tested for integrity and completeness, resulting in partial data loss and extended downtime during recovery.

7.5 Incident Response and Containment

• Delayed Detection and Response: The initial response was delayed due to the sophisticated nature of the attack, with traditional security measures failing to identify the ransomware until significant damage had occurred. The AI-powered malware’s ability to adapt and camouflage its activities contributed to this delay, highlighting the need for AI-enhanced detection and response tools.
• Forensic Analysis Challenges: The anti-forensic capabilities of the malware, including log wiping and data obfuscation, complicated the post-incident forensic analysis. Investigators had to rely on advanced techniques, such as memory forensics and machine learning-based anomaly detection, to trace the malware’s activities and identify the attack vector.

8. Recommendations Based on Technical Findings

To prevent similar incidents, the following measures are recommended:

1. AI-Powered Threat Detection: Implement AI-driven threat detection systems capable of identifying and responding to AI-powered attacks in real time. These systems should include behavioural analysis, anomaly detection, and machine learning models trained on diverse datasets.
2. Enhanced Backup Strategies: Develop a more resilient backup strategy that includes offline, air-gapped, or immutable backups. Regularly test backup systems to ensure they can be restored quickly and effectively in the event of a ransomware attack.
3. Strengthened Network Segmentation: Re-architect the network with robust segmentation and micro-segmentation to limit the spread of malware. Critical systems should be isolated, and access should be tightly controlled and monitored.
4. Regular Vulnerability Assessments: Conduct frequent vulnerability assessments and patch management audits to ensure all systems are up to date. Implement automated patch management tools where possible to reduce the window of exposure to known vulnerabilities.
5. Advanced Phishing Defences: Deploy AI-powered anti-phishing tools that can detect and block sophisticated phishing attempts. Train staff regularly on the latest phishing tactics, including how to recognize AI-generated phishing emails.

9. Conclusion

The AI empowered ransomware attack on the Indian healthcare provider in 2024 makes it clear that the threat of advanced cyber attacks has grown in the healthcare facilities. Sophisticated technical brief outlines the steps used by hackers hence underlining the importance of ongoing active and strong security. This event is a stark message to all about the importance of not only remaining alert and implementing strong investments in cybersecurity but also embarking on the formulation of measures on how best to counter such incidents with limited harm. AI is now being used by cybercriminals to increase the effectiveness of the attacks they make and it is now high time all healthcare organisations ensure that their crucial systems and data are well protected from such attacks.

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Introduction

The government has announced that the new criminal laws will come into force on 1st July 2024. The Union Government notified that three recently enacted criminal laws, viz. Bhartiya Nyaya Sanhita 2023, Bharatiya Nagarik Suraksha Sanhita 2023, and Bharatiya Sakshya Adhiniyam 2023 will be effective from 1st July 2024.  The Indian Penal Code 1860, Code of Criminal Procedure 1973, and Indian Evidence Act 1872 have been replaced by these new criminal laws.

On 23 February 2024, the Ministry of Home Affairs Announced the Effective Date of new criminal laws as follows:

1. Bharatiya Nyaya Sanhita, 2023 Effective from 1-7-2024, except Section 106(2).
2. Bharatiya Sakshya Adhiniyam, 2023 Effective from 1-7-2024.
3. Bharatiya Nagarik Suraksha Sanhita, 2023 The provisions will come into force on 1-7-2024 except the provisions of the entry relating to section 106(2) of the Bharatiya Nyaya Sanhita, 2023, in the First Schedule.

Section 106(2) Will Not Be Enforced

Truckers protested against this provision, which provides 10 years imprisonment and fines for those who cause death by rash and negligent driving of a vehicle not amounting to culpable homicide, and escape without reporting it to a police officer. As of now, the government has promised truckers and transporters that subsection 2 of Section 106 of Bharatiya Nyay Sanhita (BNS) will not come into force. This subsection deals with fatal hit-and-run cases and prescribes higher penalties for not informing authorities immediately after an accident. 

Section 106(2) of Bharatiya Nyaya Sanhita, 2023 read as follows;

106. Causing death by negligence.—

(2) Whoever causes death of any person by rash and negligent driving of vehicle not amounting to culpable homicide, and escapes without reporting it to a police officer or a Magistrate soon after the incident, shall be punished with imprisonment of either description of aterm which may extend to ten years, and shall also be liable to fine.

BHARATIYA SAKSHYA ADHINIYAM, 2023

The Bhartiya Sakshya Adhiniyam 2023 will replace the Indian Evidence Act 1872. The Act has undergone significant modification to maintain its fundamental principles for fair legal proceedings and adapt to technological advancements and changes in societal norms. This Act recognises electronic records as primary evidence under Section 57. It also allows the electronic presentation of oral evidence, enabling remote testimony and ensuring that electronic records will have the same legal effect as paper records.

Bharatiya Nagarik Suraksha Sanhita, 2023

The Bharatiya Nagarik Suraksha Sanhita, 2023 replaces the 1973 Code of Criminal Procedure, introducing certain modifications. This Act, under section 176, requires forensic investigation for crimes punished with seven years' imprisonment or more.  Section 530 of BNSS, 2023 is a newly inserted provision which envisages the use of electronic communication audio-video electronic means for trials, inquiries, proceedings, service and issuance of summons. Electronic mode is permitted for all trials, inquiries, and proceedings under section 173 of this Act. The concept of Zero FIR is also introduced under section 173(1) and mandates police stations to register the FIR, irrespective of jurisdiction.

Conclusion

India's new criminal laws are set to take effect on 1st July 2024. These laws modernise the country's legal framework, replacing outdated statutes and incorporating technological advancements. The concerns from stakeholders led to the withholding of enforcement of Section 106(2) of Bharatiya Nyaya Sanhita 2023. The new criminal laws aim to address contemporary society's complexities while upholding justice and fairness.

References

• https://www.indiatoday.in/india/video/new-criminal-laws-to-come-into-effect-from-july-1-2506664-2024-02-24
• https://www.lawrbit.com/article/ipc-crpc-evidence-act-replaced-by-new-criminal-laws/

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