Fake Profiles Wreak Havoc

Executive Summary:

A new threat being uncovered in today’s threat landscape is that while threat actors took an average of one hour and seven minutes to leverage Proof-of-Concept(PoC) exploits after they went public, now the time is at a record low of 22 minutes. This incredibly fast exploitation means that there is very limited time for organizations’ IT departments to address these issues and close the leaks before they are exploited. Cloudflare released the Application Security report which shows that the attack percentage is more often higher than the rate at which individuals invent and develop security countermeasures like the WAF rules and software patches. In one case, Cloudflare noted an attacker using a PoC-based attack within a mere 22 minutes from the moment it was released, leaving almost no time for a remediation window. 

Despite the constant growth of vulnerabilities in various applications and systems, the share of exploited vulnerabilities, which are accompanied by some level of public exploit or PoC code, has remained relatively stable over the past several years and fluctuates around 50%. These vulnerabilities with publicly known exploit code, 41% was initially attacked in the zero-day mode while of those with no known code, 84% was first attacked in the same mode. 

Modus Operandi:

The modus operandi of the attack involving the rapid weaponization of proof-of-concept (PoC) exploits is characterized by the following steps:

• Vulnerability Identification: Threat actors bring together the exploitation of a system vulnerability that may be in the software or hardware of the system; this may be a code error, design failure, or a configuration error. This is normally achieved using vulnerability scanners and test procedures that have to be performed manually. 

• Vulnerability Analysis: After the vulnerability is identified, the attackers study how it operates to determine when and how it can be triggered and what consequences that action will have. This means that one needs to analyze the details of the PoC code or system to find out the connection sequence that leads to vulnerability exploitation. 

• Exploit Code Development: Being aware of the weakness, the attackers develop a small program or script denoted as the PoC that addresses exclusively the identified vulnerability and manipulates it in a moderated manner. This particular code is meant to be utilized in showing a particular penalty, which could be unauthorized access or alteration of data. 

• Public Disclosure and Weaponization: The PoC exploit is released which is frequently done shortly after the vulnerability has been announced to the public. This makes it easier for the attackers to exploit it while waiting for the software developer to release the patch. To illustrate, Cloudflare has spotted an attacker using the PoC-based exploit 22 minutes after the publication only. 

• Attack Execution: The attackers then use the weaponized PoC exploit to attack systems which are known to be vulnerable to it. Some of the actions that are tried in this context are attempts at running remote code, unauthorized access and so on. The pace at which it happens is often much faster than the pace at which humans put in place proper security defense mechanisms, such as the WAF rules or software application fixes. 

• Targeted Operations: Sometimes, they act as if it’s a planned operation, where the attackers are selective in the system or organization to attack. For example, exploitation of CVE-2022-47966 in ManageEngine software was used during the espionage subprocess, where to perform such activity, the attackers used the mentioned vulnerability to install tools and malware connected with espionage. 

Precautions: Mitigation

Following are the mitigating measures against the PoC Exploits: 

1. Fast Patching and New Vulnerability Handling 

• Introduce proper patching procedures to address quickly the security released updates and disclosed vulnerabilities. 

• Focus should be made on the patching of those vulnerabilities that are observed to be having available PoC exploits, which often risks being exploited almost immediately.

• It is necessary to frequently check for the new vulnerability disclosures and PoC releases and have a prepared incident response plan for this purpose. 

2. Leverage AI-Powered Security Tools 

•  Employ intelligent security applications which can easily generate desirable protection rules and signatures as attackers ramp up the weaponization of PoC exploits. 

• Step up use of artificial intelligence (AI) - fueled endpoint detection and response (EDR) applications to quickly detect and mitigate the attempts. 

• Integrate Artificial Intelligence based SIEM tools to Detect & analyze Indicators of compromise to form faster reaction. 

 3. Network Segmentation and Hardening 

• Use strong networking segregation to prevent the attacker’s movement across the network and also restrict the effects of successful attacks. 

• Secure any that are accessible from the internet, and service or protocols such as RDP, CIFS, or Active directory. 

• Limit the usage of native scripting applications as much as possible because cyber attackers may exploit them. 

4. Vulnerability Disclosure and PoC Management 

• Inform the vendors of the bugs and PoC exploits and make sure there is a common understanding of when they are reported, to ensure fast response and mitigation. 

• It is suggested to incorporate mechanisms like digital signing and encryption for managing and distributing PoC exploits to prevent them from being accessed by unauthorized persons. 

• Exploits used in PoC should be simple and independent with clear and meaningful variable and function names that help reduce time spent on triage and remediation. 

5. Risk Assessment and Response to Incidents 

• Maintain constant supervision of the environment with an intention of identifying signs of a compromise, as well as, attempts of exploitation. 

• Support a frequent detection, analysis and fighting of threats, which use PoC exploits into the system and its components. 

• Regularly communicate with security researchers and vendors to understand the existing threats and how to prevent them.

Conclusion:

The rapid process of monetization of Proof of Concept (POC) exploits is one of the most innovative and constantly expanding global threats to cybersecurity at the present moment. Cyber security experts must react quickly while applying a patch, incorporate AI to their security tools, efficiently subdivide their networks and always heed their vulnerability announcements. Stronger incident response plan would aid in handling these kinds of menaces. Hence, applying measures mentioned above, the organizations will be able to prevent the acceleration of turning PoC exploits into weapons and the probability of neutral affecting cyber attacks. 

Reference:

https://www.mayrhofer.eu.org/post/vulnerability-disclosure-is-positive/

https://www.uptycs.com/blog/new-poc-exploit-backdoor-malware

https://www.balbix.com/insights/attack-vectors-and-breach-methods/

https://blog.cloudflare.com/application-security-report-2024-update

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‍Brief Overview of the EU AI Act

The EU AI Act, Regulation (EU) 2024/1689, was officially published in the EU Official Journal on 12 July 2024. This landmark legislation on Artificial Intelligence (AI) will come into force just 20 days after publication, setting harmonized rules across the EU. It amends key regulations and directives to ensure a robust framework for AI technologies.  The AI Act, a set of EU rules governing AI, has been in development for two years and now, the EU AI Act enters into force across all 27 EU Member States on 1 August 2024, with certain future deadlines tied up and the enforcement of the majority of its provisions will commence on 2 August 2026. The law prohibits certain uses of AI tools, including those that threaten citizens' rights, such as biometric categorization, untargeted scraping of faces, and systems that try to read emotions are banned in the workplace and schools, as are social scoring systems. It also prohibits the use of predictive policing tools in some instances. The law takes a phased approach to implementing the EU's AI rulebook, meaning there are various deadlines between now and then as different legal provisions will start to apply.

The framework puts different obligations on AI developers, depending on use cases and perceived risk. The bulk of AI uses will not be regulated as they are considered low-risk, but a small number of potential AI  use cases are banned under the law. High-risk use cases, such as biometric uses of AI or AI used in law enforcement, employment, education, and critical infrastructure, are allowed under the law but developers of such apps face obligations in areas like data quality and anti-bias considerations. A third risk tier also applies some lighter transparency requirements for makers of tools like AI chatbots.

In case of failure to comply with the Act, the companies in the EU providing, distributing, importing, and using AI systems and GPAI models, are subject to fines of up to EUR 35 million or seven per cent of the total worldwide annual turnover, whichever is higher.

Key highlights of EU AI Act Provisions

• The AI Act classifies AI according to its risk. It prohibits Unacceptable risks such as social scoring systems and manipulative AI. The regulation mostly addresses high-risk AI systems.
• Limited-risk AI systems are subject to lighter transparency obligations and according to the act, the developers and deployers must ensure that the end-users are aware that the interaction they are having is with AI such as Chatbots and Deepfakes. The AI Act allows the free use of minimal-risk AI. This includes the majority of AI applications currently available in the EU single market like AI-enabled video games, and spam filters, but with the advancement of Gen AI changes with regards to this might be done. The majority of obligations fall on providers (developers) of high-risk AI systems that intend to place on the market or put into service high-risk AI systems in the EU, regardless of whether they are based in the EU or a third country. And also, a third-country provider where the high-risk AI system’s output is used in the EU.
• Users are natural or legal persons who deploy an AI system in a professional capacity, not affected end-users. Users (deployers) of high-risk AI systems have some obligations, though less than providers (developers). This applies to users located in the EU, and third-country users where the AI system’s output is used in the EU.
• General purpose AI or GPAI model providers must provide technical documentation, and instructions for use, comply with the Copyright Directive, and publish a summary of the content used for training. Free and open license GPAI model providers only need to comply with copyright and publish the training data summary, unless they present a systemic risk. All providers of GPAI models that present a systemic risk – open or closed – must also conduct model evaluations, and adversarial testing, and track and report serious incidents and ensure cybersecurity protections.
• The Codes of Practice will account for international approaches. It will cover but not necessarily be limited to the obligations, particularly the relevant information to include in technical documentation for authorities and downstream providers, identification of the type and nature of systemic risks and their sources, and the modalities of risk management accounting for specific challenges in addressing risks due to the way they may emerge and materialize throughout the value chain. The AI Office may invite GPAI model providers, and relevant national competent authorities to participate in drawing up the codes, while civil society, industry, academia, downstream providers and independent experts may support the process.

Application & Timeline of Act

The EU AI Act will be fully applicable 24 months after entry into force, but some parts will be applicable sooner, for instance the ban on AI systems posing unacceptable risks will apply six months after the entry into force. The Codes of Practice will apply nine months after entry into force. Rules on general-purpose AI systems that need to comply with transparency requirements will apply 12 months after the entry into force. High-risk systems will have more time to comply with the requirements as the obligations concerning them will become applicable 36 months after the entry into force. The expected timeline for the same is:

• August 1st, 2024: The AI Act will enter into force.
• February 2025: Prohibition of certain AI systems - Chapters I (general provisions) & II (prohibited AI systems) will apply; Prohibition of certain AI systems.
• August 2025: Chapter III Section 4 (notifying authorities), Chapter V (general purpose AI models), Chapter VII (governance), Chapter XII (confidentiality and penalties), and Article 78 (confidentiality) will apply, except for Article 101 (fines for General Purpose AI providers); Requirements for new GPAI models. 
• August 2026: The whole AI Act applies, except for Article 6(1) & corresponding obligations (one of the categories of high-risk AI systems);
•  August 2027: Article 6(1) & corresponding obligations apply.

The AI Act sets out clear definitions for the different actors involved in AI, such as the providers, deployers, importers, distributors, and product manufacturers. This means all parties involved in the development, usage, import, distribution, or manufacturing of AI systems will be held accountable. Along with this, the AI Act also applies to providers and deployers of AI systems located outside of the EU, e.g., in Switzerland, if output produced by the system is intended to be used in the EU. The Act applies to any AI system within the EU that is on the market, in service, or in use, covering both AI providers (the companies selling AI systems) and AI deployers (the organizations using those systems).

In short, the AI Act will apply to different companies across the AI distribution chain, including providers, deployers, importers, and distributors (collectively referred to as “Operators”). The EU AI Act also has extraterritorial application and can also apply to companies not established in the EU, or providers outside the EU if they -make an AI system or GPAI model available on the EU market. Even if only the output generated by the AI system is used in the EU, the Act still applies to such providers and deployers. 

CyberPeace Outlook 

The EU AI Act, approved by EU lawmakers in 2024, is a landmark legislation designed to protect citizens' health, safety, and fundamental rights from potential harm caused by AI systems. The AI Act will apply to AI systems and GPAI models. The Act creates a tiered risk categorization system with various regulations and stiff penalties for noncompliance. The Act adopts a risk-based approach to AI governance, categorizing potential risks into four tiers: unacceptable, high, limited, and low. Violations of banned systems carry the highest fine: €35 million, or 7 percent of global annual revenue. It establishes transparency requirements for general-purpose AI systems. The regulation also provides specific rules for general-purpose AI (GPAI) models and lays down more stringent requirements for GPAI models with 'high-impact capabilities' that could pose a systemic risk and have a significant impact on the internal market. For high-risk AI systems, the AI Act addresses the issues of fundamental rights impact assessment and data protection impact assessment.

The EU AI Act aims to enhance trust in AI technologies by establishing clear regulatory standards governing AI. We encourage regulatory frameworks that strive to balance the desire to foster innovation with the critical need to prevent unethical practices that may cause user harm. The legislation can be seen as strengthening the EU's position as a global leader in AI innovation and developing regulatory frameworks for emerging technologies. It sets a global benchmark for regulating AI. The companies to which the act applies will need to make sure their practices align with the same. The act may inspire other nations to develop their own legislation contributing to global AI governance. The world of AI is complex and challenging, the implementation of regulatory checks, and compliance by the concerned companies, all pose a conundrum. However, in the end, balancing innovation with ethical considerations is paramount. 

At the same hand, the tech sector welcomes regulatory progress but warns that overly-rigid regulations could stifle innovation. Hence flexibility and adaptability are key to effective AI governance. The journey towards robust AI regulation has begun in major countries, and it is important that we find the right balance between safety and innovation and also take into consideration the industry reactions.

References: 

1. https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=OJ:L_202401689
2. https://www.theverge.com/2024/7/12/24197058/eu-ai-act-regulations-bans-deadline
3. https://techcrunch.com/2024/07/12/eus-ai-act-gets-published-in-blocs-official-journal-starting-clock-on-legal-deadlines/
4. https://www.wsgr.com/en/insights/eu-ai-act-to-enter-into-force-in-august.html
5. https://www.techtarget.com/searchenterpriseai/tip/Is-your-business-ready-for-the-EU-AI-Act
6. https://www.simmons-simmons.com/en/publications/clyimpowh000ouxgkw1oidakk/the-eu-ai-act-a-quick-guide

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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.