How AI Has Shifted Traditional MSP Workflows
It seems like you can’t go anywhere without hearing the words AI, LLM, or MCP. But make no mistake about it, AI has changed the way MSPs operate. A smart prompt can essentially save you hours on ticketing resolution, assist with compliance documentation, and even auto-generate client performance reports in seconds, complete with pie charts and everything.
A recent survey found that 66.7% of MSPs are already leveraging AI for IT monitoring, while 54.4% have automated ticketing and incident management. The same survey found that MSPs leveraging AI services have seen a 20-30% boost in service revenue YoY.
Who wouldn’t want to increase operational efficiency while driving down the costs associated with hiring and training additional staff, unneeded service delivery delays, and seeing their profit margins climb?
Sounds almost too good to be true. But there’s a catch. Threat actors have adopted it too.
Attackers have added new chaos to the external threat surface, figuring out new ways to launch sophisticated phishing campaigns, automate business email compromise (BEC) attacks that mimic sentiment analysis of trusted senders, and deploy advanced malware at an unprecedented scale. Many new attack paths stemming from the use of LLMs, such as prompt injection and data poisoning, present new security challenges for MSPs.
By the way, attacks on large language models (LLMs) take less than a minute to complete on average and leak sensitive data 90% of the time when successful. 42 seconds to be exact.
So, how can MSPs enjoy the benefits of AI while avoiding the risks? Before we discuss how MSPs can prevent AI-generated phishing attempts, it’s important to understand the main attack vectors and security blind spots a threat actor can exploit.
AI-Related Security Threats You Should Know About
Advanced BEC Threats: Your inbox serves as a testing environment for attackers to launch advanced phishing campaigns and other related email threats. Research showed that 40% of BEC emails are AI-generated, and spam filters don’t always catch them. To the untrained eye, a phony invoice can appear to come from a trusted vendor, complete with a company logo and polished formatting. The bank transfer, however, leads to a fraudulent account controlled by the attacker.
But that’s not all. AI adds a new layer of complexity by manipulating the context and tone of the message to make it more convincing. By the time the fraud is detected, the attacker has already changed their IP (again) and moved on to the next target. Without email security filters to detect and quarantine those suspicious emails, those inboxes remain vulnerable to BEC attacks and AI-generated phishing attempts.
Conducting routine phishing simulations can help protect those inboxes by teaching employees how to recognize the red flags and build a culture of resilience from within.
Exposed Cloud Data: Research from Tenable revealed that 70% of AI-enabled cloud workloads have critical vulnerabilities compared to only 50% of workloads without AI. Those workloads can contain sensitive information, such as training datasets, authentication credentials, and customer data. Exposure of these details can result in a serious breach, enabling attackers to gain further unauthorized access to broader cloud environments.
Another consideration is who has access to your data? A third party might inadvertently enter sensitive company information into an LLM, which could then be exposed or even used to train future models, potentially leaking proprietary data outside your organization’s control without limit or oversight. It goes without question that you should restrict and prohibit the usage of shared data. Ensure you outline this in your SLA to clearly define what data can and cannot be processed through AI tools to protect client confidentiality.
Prompt Injection Attacks: LLMs are vulnerable to prompt injection attacks, where threat actors manipulate the model’s behavior by overriding instructions or embedding harmful commands. Chatbots can also be manipulated into disclosing sensitive information or delivering malicious links that can compromise unsecured endpoints with advanced ransomware. Prompt injections impact ticket resolutions as well. Automated ticket resolutions may be trained to close critical alerts and ignore key security events, allowing critical threats to go unnoticed.
An MSP can’t properly triage security incidents if they don’t have context behind the threats or if the mitigation instructions are incorrect, resulting in a delayed response or no action at all.
AI Bias: LLMs are prone to errors. ChatGPT clearly states that it can make mistakes. Those tedious tasks you automated may produce inaccurate or biased results altogether, which can hamper decision-making processes. LLMs and AI models are trained on many datasets that may contain inherent biases or outdated information. Separating fact from fiction might not be as clear-cut as it seems, especially when it comes to threat mitigation.
AI models might prioritize certain types of security incidents based on historical data, potentially overlooking emerging threats that don’t fit established patterns. An unmitigated anomaly might escalate into a full-scale attack without a human expert to analyze the threat in a deeper context and initiate the proper containment measures.
MSPs must always validate AI-generated outputs to ensure accurate threat detection and effective response strategies.
That’s when an AI-powered, human-led MDR becomes essential.
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AI plays a significant role in simplifying routine tasks, but when it comes to threat detection, you can’t take any chances or rely on LLMs exclusively.
The Guardz MDR unifies SentinelOne capabilities and other platform detections into a single contextual system of normalized incidents, with an elite team of human-led security experts in the loop. Gain behavioral insights and integrated threat intelligence with automated response playbooks and reports.
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About Guardz
Guardz is on a mission to create a safer digital world by empowering Managed Service Providers (MSPs). Their goal is to proactively secure and insure Small and Medium Enterprises (SMEs) against ever-evolving threats while simultaneously creating new revenue streams, all on one unified platform.
About Version 2 Limited
Version 2 Digital is one of the most dynamic IT companies in Asia. The company distributes a wide range of IT products across various areas including cyber security, cloud, data protection, end points, infrastructures, system monitoring, storage, networking, business productivity and communication products.
Through an extensive network of channels, point of sales, resellers, and partnership companies, Version 2 offers quality products and services which are highly acclaimed in the market. Its customers cover a wide spectrum which include Global 1000 enterprises, regional listed companies, different vertical industries, public utilities, Government, a vast number of successful SMEs, and consumers in various Asian cities.
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