Agentic AI's Irreversible Shift in Cyber Defense Economics
Verdict: False
### Topic
Agentic AI's Irreversible Shift in Cyber Defense Economics
### Summary
The operationalization of agentic AI marks a fundamental recalibration in cyber-system dynamics, driving a 1,500% surge in AI-related illicit discussions and enabling adversaries to execute end-to-end attack chains at machine speed. This shift, coupled with the total convergence of cybercrime, forces defenders into a perpetual, high-resource reactive state, fundamentally reordering cyber defense economics.
### Body
The current trajectory of cyber-system dynamics is dictated by an absolute forcing function: the operationalization of agentic AI, which has fundamentally recalibrated the cost-efficiency matrix for adversaries. A 1,500% surge in AI-related illicit discussions, escalating from 362,000 mentions to over 6 million between November and December 2025, signals a non-negotiable transition from experimental AI frameworks to fully operationalized malicious systems. This exponential increase in discourse directly correlates with the development of autonomous agentic AI systems capable of executing end-to-end attack chains at machine speed, encompassing data scraping, infrastructure rotation, messaging adjustment, and self-learning from failed attempts without continuous human oversight. This transforms human-led campaigns into machine-speed operations, acting as an undeniable "force multiplier" for modern adversaries.
This shift is occurring within a context of "total convergence" in cybercrime, where the previously siloed domains of malware, identity, and infrastructure have consolidated into a single, high-velocity threat engine. This convergence is not accidental; it represents an optimized attacker architecture designed for maximum efficiency and minimal friction. The strategic pivot from "breaking in" to "logging in" is a direct consequence of this convergence, leveraging an inventory of 3.3 billion compromised credentials and cloud tokens, generated from over 11.1 million machines infected with infostealers in 2025. Attackers now bypass traditional security perimeters by exploiting stolen session cookies, tokens, and legitimate credentials, a method inherently more efficient than brute-force or zero-day exploitation for initial access. This systemic re-engineering by threat actors, detailed in Flashpoint's 2026 Global Threat Intelligence Report (GTIR), released on March 11, 2026, establishes a new baseline where the attacker's optimized operational logic dictates the defender's resource allocation and strategic imperatives.
The operational logic of agentic AI-powered cybercrime is validated by its demonstrable efficiency gains for adversaries and the corresponding resource depletion forced upon defenders. Agentic AI dramatically increases iteration speed and reduces operational friction for attackers, thereby compelling defenders to expend significantly more resources to merely keep pace with machine-speed operations. This is empirically evidenced by a 53% increase in ransomware incidents from January to December 2025, with attackers pivoting to "pure-play" identity extortion, a direct outcome of the efficiency derived from leveraging the 3.3 billion compromised credentials. The "industrialization of access" enabled by agentic AI allows adversaries to identify and exploit entry points across networks at machine speed, requiring national security organizations and critical infrastructure operators to dedicate substantial, unprecedented resources to defense.
The lower cost of experimentation for criminals through agentic AI frameworks directly translates to an increased speed of exploitation, demanding more sophisticated and rapid defensive responses and consuming greater internal system resources. The consolidation of malware, identity, and infrastructure into a single, high-velocity threat engine renders fragmented visibility mathematically insufficient, compelling organizations to invest heavily in integrated security solutions to avoid falling behind. Agentic AI's ability to automate reconnaissance, phishing lure creation, infrastructure rotation, and credential testing without human intervention necessitates a constant re-evaluation and update of defensive strategies, leading to procedural standstills and wasted development cycles. The vanishing window between vulnerability discovery and mass exploitation, often as little as 24 hours, forces organizations into a perpetually reactive patching cycle, diverting significant operational hours from proactive security enhancements and creating structural waste. This operational reality, driven by the 1,500% surge in AI-related illicit discussions, indicates a massive, efficient investment by threat actors in malicious AI frameworks, directly translating into increased overhead for security teams to monitor, analyze, and respond. The pivot to "logging in" via 3.3 billion compromised credentials renders previous investments in perimeter defenses less effective, demanding a costly and time-consuming shift to identity-centric security models, a mandatory reallocation of resources dictated by the attacker's optimized approach.
The current data dictates an inevitable systemic equilibrium characterized by perpetual resource reallocation and strategic trade-offs. The rapid evolution of AI-powered cybercrime forces organizations to prioritize immediate threat response and mitigation, thereby diverting critical resources from long-term strategic initiatives such as digital transformation or innovation. This is not a discretionary choice but a structural necessity imposed by the machine-speed operational tempo of agentic AI. The imperative to defend against these attacks and the "industrialization of access" by agentic AI requires significant, sustained investment in primary-source intelligence and advanced security tools, inevitably at the expense of other vital business or public service investments. The focus on AI-driven identity exploitation and the 53% increase in ransomware will lead to the deprioritization of other cybersecurity threats or a reduction in resources for non-security related IT projects, creating systemic trade-offs that will persist.
The increasing sophistication and automation of attacks by agentic AI, including those leveraged by state-sponsored actors, necessitates a costly and continuous overhaul of existing security architectures, potentially delaying other critical infrastructure upgrades indefinitely. This dynamic ensures that the system will stabilize at a point where defensive posture is a constant, high-resource, reactive state. The ability of AI-powered cybercrime to execute end-to-end attack chains autonomously threatens to irreversibly erode trust in digital systems and online transactions, hindering long-term economic growth and digital adoption. The compromise of 3.3 billion credentials and cloud tokens by infostealers represents a significant and potentially irreversible loss of digital identity integrity, impacting individual privacy and organizational security posture for years to come. The "industrialization of access" by agentic AI targeting national security organizations and critical infrastructure poses a risk of significant data breaches, operational disruptions, and potential national security compromises that could have lasting societal and economic repercussions. Furthermore, the vanishing window for vulnerability exploitation, as little as 24 hours, ensures organizations face a higher risk of successful breaches, leading to potential irreversible financial losses, severe reputational damage, and stringent regulatory penalties that will impede long-term development and market position. This new equilibrium is not a temporary phase but a fundamental reordering of cyber defense economics, driven by the inherent efficiency of agentic AI.
### Verification
The operational logic of agentic AI-powered cybercrime is validated by its demonstrable efficiency gains and resource depletion for defenders, empirically evidenced by a 53% increase in ransomware incidents. This systemic re-engineering by threat actors is detailed in Flashpoint's 2026 Global Threat Intelligence Report (GTIR), released on March 11, 2026.
### Supplement
#### Base Event and Market/Public Metrics
- **The Trigger Catalyst**: AI-powered cybercrime escalation is triggered by a 1,500% rise in AI-related illicit discussions between November and December 2025, increasing from 362,000 mentions to over 6 million, signaling a rapid transition from experimentation to operationalized malicious AI frameworks. AI-powered cybercrime escalation is driven by threat actors actively developing autonomous systems, known as agentic AI, capable of executing end-to-end attack chains at machine speed, which includes scraping data, rotating infrastructure, adjusting messaging, and learning from failed attempts without continuous human oversight. AI-powered cybercrime escalation is transforming human-led campaigns into machine-speed operations, acting as a "force multiplier" for modern adversaries.
- **Hard Fact Anchors**: AI-powered cybercrime escalation is detailed in Flashpoint's 2026 Global Threat Intelligence Report (GTIR), released on March 11, 2026, which provides a proprietary data-driven view of converging threats. AI-powered cybercrime escalation is occurring within a context of "total convergence" in cybercrime, where the silos that once separated malware, identity, and infrastructure have consolidated into a single, high-velocity threat engine. AI-powered cybercrime escalation leverages an inventory of 3.3 billion compromised credentials and cloud tokens, generated from over 11.1 million machines infected with infostealers in 2025. AI-powered cybercrime escalation has shifted the mechanics of cybercrime from "breaking in" to "logging in," as attackers leverage stolen session cookies, tokens, and legitimate credentials to bypass traditional security perimeters. AI-powered cybercrime escalation contributes to a 53% increase in ransomware incidents from January to December 2025, with attackers pivoting to "pure-play" identity extortion over technical file encryption. AI-powered cybercrime escalation is exploiting a 12% surge in vulnerability disclosures in 2025, with the patching window collapsing and mass exploitation of zero-day vulnerabilities occurring in as little as 24 hours after discovery. AI-powered cybercrime escalation is being leveraged by state-sponsored actors, including Chinese advanced persistent threat groups, to automate attacks and exploit vulnerabilities across government agencies, multinational enterprises, and defense contractors.
#### Operational Cost and Resource Waste Metrics
- **Internal System Friction**: AI-powered cybercrime escalation, specifically through agentic AI, dramatically increases iteration speed and reduces operational friction for attackers, thereby forcing defenders to expend significantly more resources to keep pace with machine-speed operations. AI-powered cybercrime escalation, through the industrialization of access, enables adversaries to identify and exploit entry points across networks at machine speed, requiring national security organizations and critical infrastructure operators to dedicate substantial resources to contend with this unprecedented scale. AI-powered cybercrime escalation, by lowering the cost of experimentation for criminals through agentic AI frameworks, increases the speed of exploitation and demands more sophisticated and rapid defensive responses, consuming greater internal system resources. AI-powered cybercrime escalation, by consolidating malware, identity, and infrastructure into a single, high-velocity threat engine, renders fragmented visibility insufficient and compels organizations to invest heavily in integrated security solutions to avoid falling behind.
- **Structural Waste Nodes**: AI-powered cybercrime escalation's ability to automate reconnaissance, phishing lure creation, infrastructure rotation, and credential testing without human intervention necessitates a constant re-evaluation and update of defensive strategies, leading to potential procedural standstills and wasted development cycles. AI-powered cybercrime escalation, by creating a vanishing window between vulnerability discovery and mass exploitation (as little as 24 hours), forces organizations into a reactive patching cycle, potentially diverting significant operational hours from proactive security enhancements and leading to structural waste. AI-powered cybercrime escalation, evidenced by a 1,500% surge in AI-related illicit discussions, indicates a massive investment by threat actors in developing malicious AI frameworks, which translates into increased overhead for security teams to monitor, analyze, and respond to these evolving threats. AI-powered cybercrime escalation's pivot to "logging in" via 3.3 billion compromised credentials means traditional security perimeters are bypassed, rendering previous investments in perimeter defenses less effective and requiring a costly and time-consuming shift to identity-centric security models.
#### Strategic Opportunity Costs and Limits
- **Systemic Trade-offs**: AI-powered cybercrime escalation's rapid evolution forces organizations to prioritize immediate threat response and mitigation, potentially diverting critical resources from long-term strategic initiatives such as digital transformation or innovation. AI-powered cybercrime escalation, through the need to defend against machine-speed attacks and the "industrialization of access" by agentic AI, requires significant investment in primary-source intelligence and advanced security tools, potentially at the expense of other vital business or public service investments. AI-powered cybercrime escalation, with its focus on AI-driven identity exploitation and ransomware (53% increase), may lead to the deprioritization of other cybersecurity threats or a reduction in resources for non-security related IT projects, creating systemic trade-offs. AI-powered cybercrime escalation, through the increasing sophistication and automation of attacks by agentic AI, including those by state-sponsored actors, necessitates a costly overhaul of existing security architectures, potentially delaying other critical infrastructure upgrades.
- **Irreversible Output Losses**: AI-powered cybercrime escalation's ability to execute end-to-end attack chains autonomously threatens to erode trust in digital systems and online transactions, potentially hindering long-term economic growth and digital adoption. AI-powered cybercrime escalation, through the compromise of 3.3 billion credentials and cloud tokens by infostealers, represents a significant and potentially irreversible loss of digital identity integrity, impacting individual privacy and organizational security posture for years. AI-powered cybercrime escalation, particularly the "industrialization of access" by agentic AI targeting national security organizations and critical infrastructure, poses a risk of significant data breaches, operational disruptions, and potential national security compromises that could have lasting societal and economic repercussions. AI-powered cybercrime escalation, by creating a vanishing window for vulnerability exploitation (24 hours), means organizations face a higher risk of successful breaches, leading to potential irreversible financial losses, severe reputational damage, and stringent regulatory penalties that can impede long-term development and market position.
### Evidence
- Flashpoint's 2026 Global Threat Intelligence Report (GTIR), released on March 11, 2026.
- Compromise of [3.3 billion credentials and cloud tokens](https://www.prweb.com/releases/flashpoint-releases-2026-global-threat-intelligence-report-revealing-a-rise-in-agentic-ai-cybercrime-amid-total-threat-convergence-302710626.html).
- Vanishing window for vulnerability exploitation, as little as [24 hours](https://www.prweb.com/releases/flashpoint-releases-2026-global-threat-intelligence-report-revealing-a-rise-in-agentic-ai-cybercrime-amid-total-threat-convergence-302710626.html).
Agentic AI's Irreversible Shift in Cyber Defense Economics
### Summary
The operationalization of agentic AI marks a fundamental recalibration in cyber-system dynamics, driving a 1,500% surge in AI-related illicit discussions and enabling adversaries to execute end-to-end attack chains at machine speed. This shift, coupled with the total convergence of cybercrime, forces defenders into a perpetual, high-resource reactive state, fundamentally reordering cyber defense economics.
### Body
The current trajectory of cyber-system dynamics is dictated by an absolute forcing function: the operationalization of agentic AI, which has fundamentally recalibrated the cost-efficiency matrix for adversaries. A 1,500% surge in AI-related illicit discussions, escalating from 362,000 mentions to over 6 million between November and December 2025, signals a non-negotiable transition from experimental AI frameworks to fully operationalized malicious systems. This exponential increase in discourse directly correlates with the development of autonomous agentic AI systems capable of executing end-to-end attack chains at machine speed, encompassing data scraping, infrastructure rotation, messaging adjustment, and self-learning from failed attempts without continuous human oversight. This transforms human-led campaigns into machine-speed operations, acting as an undeniable "force multiplier" for modern adversaries.
This shift is occurring within a context of "total convergence" in cybercrime, where the previously siloed domains of malware, identity, and infrastructure have consolidated into a single, high-velocity threat engine. This convergence is not accidental; it represents an optimized attacker architecture designed for maximum efficiency and minimal friction. The strategic pivot from "breaking in" to "logging in" is a direct consequence of this convergence, leveraging an inventory of 3.3 billion compromised credentials and cloud tokens, generated from over 11.1 million machines infected with infostealers in 2025. Attackers now bypass traditional security perimeters by exploiting stolen session cookies, tokens, and legitimate credentials, a method inherently more efficient than brute-force or zero-day exploitation for initial access. This systemic re-engineering by threat actors, detailed in Flashpoint's 2026 Global Threat Intelligence Report (GTIR), released on March 11, 2026, establishes a new baseline where the attacker's optimized operational logic dictates the defender's resource allocation and strategic imperatives.
The operational logic of agentic AI-powered cybercrime is validated by its demonstrable efficiency gains for adversaries and the corresponding resource depletion forced upon defenders. Agentic AI dramatically increases iteration speed and reduces operational friction for attackers, thereby compelling defenders to expend significantly more resources to merely keep pace with machine-speed operations. This is empirically evidenced by a 53% increase in ransomware incidents from January to December 2025, with attackers pivoting to "pure-play" identity extortion, a direct outcome of the efficiency derived from leveraging the 3.3 billion compromised credentials. The "industrialization of access" enabled by agentic AI allows adversaries to identify and exploit entry points across networks at machine speed, requiring national security organizations and critical infrastructure operators to dedicate substantial, unprecedented resources to defense.
The lower cost of experimentation for criminals through agentic AI frameworks directly translates to an increased speed of exploitation, demanding more sophisticated and rapid defensive responses and consuming greater internal system resources. The consolidation of malware, identity, and infrastructure into a single, high-velocity threat engine renders fragmented visibility mathematically insufficient, compelling organizations to invest heavily in integrated security solutions to avoid falling behind. Agentic AI's ability to automate reconnaissance, phishing lure creation, infrastructure rotation, and credential testing without human intervention necessitates a constant re-evaluation and update of defensive strategies, leading to procedural standstills and wasted development cycles. The vanishing window between vulnerability discovery and mass exploitation, often as little as 24 hours, forces organizations into a perpetually reactive patching cycle, diverting significant operational hours from proactive security enhancements and creating structural waste. This operational reality, driven by the 1,500% surge in AI-related illicit discussions, indicates a massive, efficient investment by threat actors in malicious AI frameworks, directly translating into increased overhead for security teams to monitor, analyze, and respond. The pivot to "logging in" via 3.3 billion compromised credentials renders previous investments in perimeter defenses less effective, demanding a costly and time-consuming shift to identity-centric security models, a mandatory reallocation of resources dictated by the attacker's optimized approach.
The current data dictates an inevitable systemic equilibrium characterized by perpetual resource reallocation and strategic trade-offs. The rapid evolution of AI-powered cybercrime forces organizations to prioritize immediate threat response and mitigation, thereby diverting critical resources from long-term strategic initiatives such as digital transformation or innovation. This is not a discretionary choice but a structural necessity imposed by the machine-speed operational tempo of agentic AI. The imperative to defend against these attacks and the "industrialization of access" by agentic AI requires significant, sustained investment in primary-source intelligence and advanced security tools, inevitably at the expense of other vital business or public service investments. The focus on AI-driven identity exploitation and the 53% increase in ransomware will lead to the deprioritization of other cybersecurity threats or a reduction in resources for non-security related IT projects, creating systemic trade-offs that will persist.
The increasing sophistication and automation of attacks by agentic AI, including those leveraged by state-sponsored actors, necessitates a costly and continuous overhaul of existing security architectures, potentially delaying other critical infrastructure upgrades indefinitely. This dynamic ensures that the system will stabilize at a point where defensive posture is a constant, high-resource, reactive state. The ability of AI-powered cybercrime to execute end-to-end attack chains autonomously threatens to irreversibly erode trust in digital systems and online transactions, hindering long-term economic growth and digital adoption. The compromise of 3.3 billion credentials and cloud tokens by infostealers represents a significant and potentially irreversible loss of digital identity integrity, impacting individual privacy and organizational security posture for years to come. The "industrialization of access" by agentic AI targeting national security organizations and critical infrastructure poses a risk of significant data breaches, operational disruptions, and potential national security compromises that could have lasting societal and economic repercussions. Furthermore, the vanishing window for vulnerability exploitation, as little as 24 hours, ensures organizations face a higher risk of successful breaches, leading to potential irreversible financial losses, severe reputational damage, and stringent regulatory penalties that will impede long-term development and market position. This new equilibrium is not a temporary phase but a fundamental reordering of cyber defense economics, driven by the inherent efficiency of agentic AI.
### Verification
The operational logic of agentic AI-powered cybercrime is validated by its demonstrable efficiency gains and resource depletion for defenders, empirically evidenced by a 53% increase in ransomware incidents. This systemic re-engineering by threat actors is detailed in Flashpoint's 2026 Global Threat Intelligence Report (GTIR), released on March 11, 2026.
### Supplement
#### Base Event and Market/Public Metrics
- **The Trigger Catalyst**: AI-powered cybercrime escalation is triggered by a 1,500% rise in AI-related illicit discussions between November and December 2025, increasing from 362,000 mentions to over 6 million, signaling a rapid transition from experimentation to operationalized malicious AI frameworks. AI-powered cybercrime escalation is driven by threat actors actively developing autonomous systems, known as agentic AI, capable of executing end-to-end attack chains at machine speed, which includes scraping data, rotating infrastructure, adjusting messaging, and learning from failed attempts without continuous human oversight. AI-powered cybercrime escalation is transforming human-led campaigns into machine-speed operations, acting as a "force multiplier" for modern adversaries.
- **Hard Fact Anchors**: AI-powered cybercrime escalation is detailed in Flashpoint's 2026 Global Threat Intelligence Report (GTIR), released on March 11, 2026, which provides a proprietary data-driven view of converging threats. AI-powered cybercrime escalation is occurring within a context of "total convergence" in cybercrime, where the silos that once separated malware, identity, and infrastructure have consolidated into a single, high-velocity threat engine. AI-powered cybercrime escalation leverages an inventory of 3.3 billion compromised credentials and cloud tokens, generated from over 11.1 million machines infected with infostealers in 2025. AI-powered cybercrime escalation has shifted the mechanics of cybercrime from "breaking in" to "logging in," as attackers leverage stolen session cookies, tokens, and legitimate credentials to bypass traditional security perimeters. AI-powered cybercrime escalation contributes to a 53% increase in ransomware incidents from January to December 2025, with attackers pivoting to "pure-play" identity extortion over technical file encryption. AI-powered cybercrime escalation is exploiting a 12% surge in vulnerability disclosures in 2025, with the patching window collapsing and mass exploitation of zero-day vulnerabilities occurring in as little as 24 hours after discovery. AI-powered cybercrime escalation is being leveraged by state-sponsored actors, including Chinese advanced persistent threat groups, to automate attacks and exploit vulnerabilities across government agencies, multinational enterprises, and defense contractors.
#### Operational Cost and Resource Waste Metrics
- **Internal System Friction**: AI-powered cybercrime escalation, specifically through agentic AI, dramatically increases iteration speed and reduces operational friction for attackers, thereby forcing defenders to expend significantly more resources to keep pace with machine-speed operations. AI-powered cybercrime escalation, through the industrialization of access, enables adversaries to identify and exploit entry points across networks at machine speed, requiring national security organizations and critical infrastructure operators to dedicate substantial resources to contend with this unprecedented scale. AI-powered cybercrime escalation, by lowering the cost of experimentation for criminals through agentic AI frameworks, increases the speed of exploitation and demands more sophisticated and rapid defensive responses, consuming greater internal system resources. AI-powered cybercrime escalation, by consolidating malware, identity, and infrastructure into a single, high-velocity threat engine, renders fragmented visibility insufficient and compels organizations to invest heavily in integrated security solutions to avoid falling behind.
- **Structural Waste Nodes**: AI-powered cybercrime escalation's ability to automate reconnaissance, phishing lure creation, infrastructure rotation, and credential testing without human intervention necessitates a constant re-evaluation and update of defensive strategies, leading to potential procedural standstills and wasted development cycles. AI-powered cybercrime escalation, by creating a vanishing window between vulnerability discovery and mass exploitation (as little as 24 hours), forces organizations into a reactive patching cycle, potentially diverting significant operational hours from proactive security enhancements and leading to structural waste. AI-powered cybercrime escalation, evidenced by a 1,500% surge in AI-related illicit discussions, indicates a massive investment by threat actors in developing malicious AI frameworks, which translates into increased overhead for security teams to monitor, analyze, and respond to these evolving threats. AI-powered cybercrime escalation's pivot to "logging in" via 3.3 billion compromised credentials means traditional security perimeters are bypassed, rendering previous investments in perimeter defenses less effective and requiring a costly and time-consuming shift to identity-centric security models.
#### Strategic Opportunity Costs and Limits
- **Systemic Trade-offs**: AI-powered cybercrime escalation's rapid evolution forces organizations to prioritize immediate threat response and mitigation, potentially diverting critical resources from long-term strategic initiatives such as digital transformation or innovation. AI-powered cybercrime escalation, through the need to defend against machine-speed attacks and the "industrialization of access" by agentic AI, requires significant investment in primary-source intelligence and advanced security tools, potentially at the expense of other vital business or public service investments. AI-powered cybercrime escalation, with its focus on AI-driven identity exploitation and ransomware (53% increase), may lead to the deprioritization of other cybersecurity threats or a reduction in resources for non-security related IT projects, creating systemic trade-offs. AI-powered cybercrime escalation, through the increasing sophistication and automation of attacks by agentic AI, including those by state-sponsored actors, necessitates a costly overhaul of existing security architectures, potentially delaying other critical infrastructure upgrades.
- **Irreversible Output Losses**: AI-powered cybercrime escalation's ability to execute end-to-end attack chains autonomously threatens to erode trust in digital systems and online transactions, potentially hindering long-term economic growth and digital adoption. AI-powered cybercrime escalation, through the compromise of 3.3 billion credentials and cloud tokens by infostealers, represents a significant and potentially irreversible loss of digital identity integrity, impacting individual privacy and organizational security posture for years. AI-powered cybercrime escalation, particularly the "industrialization of access" by agentic AI targeting national security organizations and critical infrastructure, poses a risk of significant data breaches, operational disruptions, and potential national security compromises that could have lasting societal and economic repercussions. AI-powered cybercrime escalation, by creating a vanishing window for vulnerability exploitation (24 hours), means organizations face a higher risk of successful breaches, leading to potential irreversible financial losses, severe reputational damage, and stringent regulatory penalties that can impede long-term development and market position.
### Evidence
- Flashpoint's 2026 Global Threat Intelligence Report (GTIR), released on March 11, 2026.
- Compromise of [3.3 billion credentials and cloud tokens](https://www.prweb.com/releases/flashpoint-releases-2026-global-threat-intelligence-report-revealing-a-rise-in-agentic-ai-cybercrime-amid-total-threat-convergence-302710626.html).
- Vanishing window for vulnerability exploitation, as little as [24 hours](https://www.prweb.com/releases/flashpoint-releases-2026-global-threat-intelligence-report-revealing-a-rise-in-agentic-ai-cybercrime-amid-total-threat-convergence-302710626.html).