E-Business
Improve Security Posture Enabled Endpoint Detection and Response
By Jimi Falaiye
Cybercrime is big business and hackers are continually looking for new attack vectors. SophosLabs team see 400,000 new malicious samples every day; this does not mean 400,000 programmers writing code.
It means heavily automated systems. The result is bespoke malware – a virus written just for you. With that reality, the best line of defense is to use a multi-layered security strategy to work to protect organisations against both known and unknown threats.
The best endpoint technologies will protect organisations against the majority of malware and threats impacting their organisation.
But as the threat landscape evolves and cybercriminals continue to morph attacks and work to find new security holes to access organisations, the unknown minority becomes important.
Endpoint detection and response tools are about detecting that minority.
EDR tools are built to supplement endpoint security with increased detection, investigation, and response capabilities. However, EDR tools can make it difficult to understand how exactly they can be used and why they are needed.
Making matters worse, today’s EDR solutions often struggle to provide value for many organisations as they can be difficult to use, lack sufficient protection capabilities, and are resource intensive.
The good news is deep learning enabled EDR tools provide the easiest way for organisations to answer the tough questions about security incidents.
Here are the ways how deep learning enabled EDR tools help organisations to add an additional layer to their security posture.
EDR helps in generating clear view of an organization’s security posture
The hardest question for most IT and security teams is “are we secure right now?” This is because most networks have sizable blind spots that make IT and security teams struggle to see what is going on inside their environments. Lack of visibility is the primary reason why organisations struggle to understand the scope and impact of attacks.
This often manifests itself when an incident occurs and the team assumes they are safe because that incident was detected. Deep learning enabled EDR provides this additional insight as well as determines if other machines were impacted.
Generating a clear view of an organization’s security posture provides the benefit of being able to report on compliance status. This information will help identify areas that may be vulnerable to attacks. It also allows administrators to determine if the scope of an attack has impacted areas where sensitive data is housed.
It provides additional layer of detection
When it comes to cybersecurity, even the most advanced tools can be defeated given enough time and resources, making it difficult to truly understand when attacks are happening. Organisations often rely solely on prevention to stay protected, and while prevention is critical, EDR offers another layer of detection capabilities to potentially find incidents that have gone unnoticed.
Organisations can leverage EDR to detect attacks by searching for indicators of compromise (IOCs). This is a quick and straightforward way to hunt for attacks that may have been missed.
It increases response time to potential incidents
Once incidents are detected, IT and security teams usually scramble to remediate them as fast as possible to reduce the risk of attacks spreading and to limit any potential damage. On average, security and IT teams spend more than three hours trying to remediate each incident. EDR can speed this up significantly.
The first step an analyst might take during the incident response process would be to stop an attack from spreading. Analysts will often do this before investigating, buying time while they determine the best course of action.
The investigation process can be a slow and painful one. This of course assumes an investigation occurs at all. Incident response traditionally relies heavily on highly-skilled human analysts.
Most EDR tools also rely heavily on analysts to know which questions to ask and how to interpret the answers. However, with deep learning enabled EDR, security teams of all skill levels can quickly respond to security incidents thanks to guided investigations that offer suggested next steps, clear visual attack representations, and built-in expertise.
It adds expertise without adding headcount
By a large margin, organisations looking to add endpoint detection and response capabilities cite “staff knowledge” as the top impediment to EDR adoption. To combat the staff knowledge gap deep learning enabled EDR replicates the capabilities associated with hard-to-find analysts. It leverages machine learning to integrate deep security insight, so organisations can add expertise without having to add staff.
It helps in understanding how an attack happened and how to stop it from happening again
Threat cases, included with EDR, spotlight all the events that led up to a detection, making it easy to understand which files, processes, and registry keys were touched by the malware to determine the impact of an attack.
More importantly, by understanding the root cause of an attack, the IT team will be much more likely to prevent it from ever happening again.
Jimi Falaiye is the Country Manager Nigeria, Sophos.
In a sobering revelation of the evolving threat landscape facing the digital asset ecosystem, blockchain intelligence firm TRM Labs has disclosed that over $2.1 billion worth of cryptocurrency was stolen in the first half of 2025 alone, spanning at least 75 high-profile hacks and exploits.
This staggering figure marks a 10 per cent surge over the previous first-half record set in 2022 and nearly eclipses the total stolen in all of 2024.
But beyond the monetary scale, the report reveals a deeper concern: a growing trend of state-sponsored cyber aggression weaponising crypto assets for strategic and geopolitical purposes.
The most devastating breach to date occurred in February when Dubai-based exchange Bybit lost $1.5 billion—the largest crypto heist in history.
TRM Labs attributes the attack to North Korean state actors, noting that the incident alone accounted for nearly 70 percent of total losses during the period and doubled the average hack size to $30 million.
“The Bybit hack redefined the threat landscape,” the report stated.
“It exemplifies how digital asset theft has transcended criminal opportunism and morphed into a tool of statecraft.”
Indeed, North Korea-linked entities were responsible for an estimated $1.6 billion of the total stolen, further entrenching Pyongyang’s status as the most prolific nation-state threat actor in the crypto sphere.
Yet the menace is diversifying. On June 18, Iranian crypto exchange Nobitex was breached for over $90 million by a group reportedly linked to Israel, Gonjeshke Darande (Predatory Sparrow).
Unusually, the stolen funds were routed to unusable vanity addresses, underscoring symbolic and political motives rather than financial gain.
TRM Labs flagged this as a “disturbing shift,” with digital asset theft increasingly deployed as a weapon in asymmetric geopolitical conflict.
The report also found that more than 80 percent of losses stemmed from infrastructure breaches, including private key theft, seed phrase leaks, and front-end compromises— attacks typically ten times costlier than other vectors.
Meanwhile, DeFi exploits such as flash loan manipulations accounted for 12 percent of losses, reflecting persistent smart contract vulnerabilities despite years of scrutiny.
As digital currencies become enmeshed in global rivalries, TRM Labs warns that conventional cybersecurity approaches are now inadequate.
“Massive breaches, often tied to nation-state operations, require a new defence paradigm,” the firm asserted, urging industrywide adoption of advanced safeguards and cross-border collaboration among regulators and law enforcement.
Corporate Affairs Commission (CAC) has inaugurated the pilot take-off of its new Artificial Intelligence (AI)-powered registration portal.
A statement issued by the commission explained that Malam Hussaini Magaji, registrar-general of the CAC, made the announcement during the 2025 Stakeholders Forum in Port Harcourt.
According to him, “the initiative is a major milestone in Nigeria’s business facilitation drive.”
The Registrar further explained that the upgraded portal marks a complete overhaul of the Company Registration Portal (CRP), saying that it comes with advanced features designed to simplify and speed up business registration.
The new system, according to him, allows for instant name reservation approvals, likening the ease to creating an email account, and stressing that the AI-powered platform could suggest available alternatives to business names and approve them immediately.
Another innovation, he stated, is the ability to register a business using only the National Identification Number (NIN) of a director or proprietor, pointing out that there is an ambitious target of completing business registration and certificate generation within 30 minutes, subject to real-time NIN validation.
Bitget has launched its institutional services in Nigeria, offering fintech companies a robust platform to build innovative solutions on top of Bitget’s suite of institutional-grade offerings.
Gracy Chen, CEO, Bitget, in a statement said, “Our goal is to empower Nigerian businesses to innovate and leverage blockchain for wealth creation opportunities, hence, the institutional services empower fintech leaders with tailored solutions, as the offerings designed to cater for the unique operational needs of institutional clients, enabling businesses to embed trading functionalities like spot and futures markets, wallet management, and more, directly into their platforms.
“The Key services include White-label Broker Services which enabled Fintech companies to deploy customized crypto exchanges using Bitget’s infrastructure while managing branding and users independently. There is also API Solutions that can make the Developers to integrate trading functionality via APIs for spot, margin, and derivatives markets, ensuring fast execution and seamless experiences for end users.”
Chen added, “The ND Broker Model provides clients with complete autonomy over user-facing platforms, offering exclusive front-end flexibility while relying on Bitget for back-end market liquidity. Clients are able to employ Protection Fund and Proof of Reserves of over $600million secured in the Bitget Protection Fund and real-time Proof of Reserves, which gives clients assurance of maximum transparency and security.”
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