Deepen Desai is most useful for translating AI security, phishing, and security operations research into defensive priorities.
Best for
A security vendor seeking a practitioner voice for co-authored threat research or a webinar.
Not for
A vendor wanting an independent, vendor-neutral paid reviewer to rank competing endpoint or SecOps platforms.
Key takeaways
AI models can build complex exploit paths, so defense must assume machine-speed attacks.
Phishing volume is falling but methods improve; priorities include segmentation, deception, phishing-resistant MFA, awareness.
Security operations should close the loop rather than add more tools.
Check first: Confirm whether Zscaler's security organization can approve the partnership and if an independent booking route exists.
Main ideas
AI models can now build attacks, so defense has to assume machine-speed exploit paths · Phishing is falling in volume but improving in method, and the countermeasures are a short, named list · Security operations needs to be rebuilt around closing the loop, not adding more tools
In these posts, Deepen Desai discusses cybersecurity at Zscaler, especially AI-driven threats, threat research, and security operations.
They connect concrete attack patterns—such as phishing aimed at session tokens and AI models constructing exploit paths—with practical defensive priorities.
They also share a product launch and announce a webinar, alongside research-focused commentary.
Desai’s clearest contribution in this sample is translating technical security developments into implications for defenders.
In a post about frontier-model testing, they describe how multi-step reasoning can build complex exploit paths, why architectural context affects accuracy, and why context should be bounded.
In a separate post about phishing research, they move from changing attack tactics to three stated priorities: segmentation and deception, phishing-resistant MFA, and ongoing security awareness.
This combination gives readers both a view of how threats are changing and specific defenses to consider.
The sample also includes product-launch material, more directly tied to Zscaler’s offering than the research posts.
Follow them for a mix of threat analysis and security-operations perspectives.
Deepen Desai argues that AI has changed what attackers can do — automating more stages, chaining exploits, and compressing defenders' response time — while many security operations teams still face fragmented tools, incomplete visibility, and manual steps.
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They repeatedly call for a layered response: Zero Trust architecture with segmentation and deception to limit blast radius, exposure management, phishing-resistant multi-factor authentication, continuous awareness training, and closed-loop remediation that turns detection into action. Firsthand testing of frontier models and analysis of the annual phishing data ground those recommendations.
AI models can now build attacks, so defense has to assume machine-speed exploit paths
Deepen Desai argues that frontier AI has moved beyond scanning for known vulnerabilities: with multi-step reasoning, a model can autonomously construct a complex exploit path.
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Two observations support that claim: architectural context significantly improves a model's accuracy when exploiting a target, but that context should ground it in its own environment, not extend beyond it. The conclusion calls for a combination of controls, not a single product: AI-powered scanning across the software development lifecycle and CI/CD pipeline, Zero Trust architecture, AI-powered exposure management, and deception technology.
Zscaler's security team obtained early access to frontier models through Anthropic's Project Glasswing and OpenAI's Trusted Access for Cyber program. It tested Anthropic Mythos and OpenAI GPT 5.5 Cyber against real attack and defense scenarios, then published three numbered observations.
The post pairs enthusiasm for testing and using frontier models with a clear limit: keep the context given to them narrowly bounded.
Phishing is falling in volume but improving in method, and the countermeasures are a short, named list
Deepen Desai reads the annual Zscaler ThreatLabz phishing and initial access data as a story of quality over quantity.
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Volume dropped about 20% year over year, but campaigns increasingly combine email with phone calls, voice, or text-based social engineering.
Attackers are moving beyond credential theft toward session tokens and rapid post-compromise action, while agents are being phished by humans and other agents.
The report sets out three concrete priorities in response to these changing methods.
Deepen Desai draws three priorities from the report: Zero Trust architecture with segmentation and deception to reduce blast radius, phishing-resistant multi-factor authentication, and continuous security awareness training. The full report includes an agent-phishing example.
Security operations needs to be rebuilt around closing the loop, not adding more tools
Deepen Desai argues that the traditional SOC model was already strained and is now breaking down: fragmented tools, incomplete visibility, high data-ingestion costs, and too many manual steps leave responders too slow against automated attacks.
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The proposed fix closes the gap between signal and action: unified exposure and threat management in one platform; operational access to inline telemetry across network, identity, endpoint, cloud, AI, and deception; specialized AI agents shaped by frontline SOC, managed detection and response, and threat-hunting experience; and closed-loop remediation through the Zero Trust Exchange, turning detection into real-time action.
In the announcement of Zscaler's Agentic Security Operations offering, Deepen Desai credits customers, teams, and partners and names participants in the launch conversation: Brett Andrews from Anthropic, Sameer Ratolikar from HDFC Bank, Andrea Licciardi from MAIRE, and Allie Mellen from Forrester.
Practical preparation should come from tested research partnerships, presented with named colleagues
Deepen Desai turns threat research into practitioner guidance by naming the shift, citing research programs that granted early access, and promising practical preparation rather than theory.
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Webinars and shared research bring the work to practitioners alongside named colleagues.
A Zscaler webinar announcement pairs Deepen Desai with colleagues Dhawal Sharma, Zoltan Kovacs, and Amir Moin.
It focuses on autonomous vulnerability discovery and machine-speed attack orchestration, drawing on work with Anthropic's Project Glasswing and OpenAI Daybreak, and includes a registration link.
The announcement does not describe the session itself; ask for its agenda or recording before assessing its practical value.
It answers the newcomer's question "what does Deepen Desai actually talk about day to day?" in a single pass: current attack trends, who they affect, and the three defenses Desai puts first.
Deepen Desai walks through findings from the ThreatLabz 2026 Phishing and Initial Access Report.
Four points stand out: phishing volume fell about 20% year over year, but quality rose; phishing is increasingly “multi-dimensional,” mixing email with phone calls, voice, or text messages; attackers are moving beyond simple credential theft to stealing session tokens and acting quickly after a compromise; and AI agents are now being phished by humans and by other agents, with a worked example in the report.
Desai closes with three priorities: Zero Trust architecture with segmentation and deception to limit blast radius, phishing-resistant multi-factor authentication, and continuous security awareness training.
The post links to the full report.
For brands planning a campaign
A vendor seeking a webinar or co-authored research partner has a ready-made format here: a report walkthrough paired with named defense priorities. The angle of “agents getting phished by humans and other agents” is the post’s most unfamiliar point and the clearest hook for a joint research brief.
This is the most firsthand item in the set: Desai’s team conducts the testing rather than summarizing someone else’s report, and the post explains concretely why AI changes the threat model.
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Deepen Desai describes Zscaler’s security team getting early access to frontier AI models through Anthropic’s Project Glasswing and OpenAI’s Trusted Access for Cyber program, then testing them against real attack and defense scenarios.
The post reports three observations: multi-step reasoning lets a model build complex exploit paths on its own instead of only scanning for known vulnerabilities; architectural context meaningfully improves exploit accuracy; and context should be limited to grounding the model in its environment.
The recommended defense combines AI-powered scanning in the software development lifecycle and CI/CD pipeline, Zero Trust architecture, AI-powered exposure management, and deception technology.
The post links to a longer blog.
For brands planning a campaign
A co-authored threat research collaboration could test frontier models under controlled conditions, with early-access arrangements as the differentiator. The three numbered observations give a joint piece a clear structure: exploit-path reasoning, architectural context, and context boundaries.
Read this for the clearest statement of Deepen Desai's framing of the problem.
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It answers "why does this person think security operations needs to change?" and shows the vocabulary they use with a product audience.
Deepen Desai announces the launch of Zscaler’s Agentic Security Operations solution and explains the reasoning behind it: attackers are automating more stages, chaining exploits, and using AI to shorten defenders’ response time, while many security operations centers still rely on fragmented tools, incomplete visibility, high data-ingestion costs, and manual steps.
The launch covers unified exposure and threat management in one platform, operational access to inline telemetry across network, identity, endpoint, cloud, AI, and deception, specialized AI agents shaped by more than a decade of SOC, MDR, and threat-hunting work, and closed-loop remediation through the Zero Trust Exchange.
Desai credits customers, teams, partners, and named participants from Anthropic, HDFC Bank, MAIRE, and Forrester, and links to an event recording.
For brands planning a campaign
This launch-narrative post shows what Desai will publicly put their name to and who they share a stage with. Because the content is product-led, the report and frontier-model posts offer more distinctive material for a joint webinar.
Short and forward-looking, this confirms a pattern across the other items: Desai appears publicly alongside named colleagues and turns current threat research into guidance for practitioners.
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Deepen Desai announces an upcoming Zscaler webinar with colleagues Dhawal Sharma, Zoltan Kovacs, and Amir Moin, framed around autonomous vulnerability discovery and machine-speed attack orchestration.
The session draws on Zscaler’s work with Anthropic’s Project Glasswing and OpenAI Daybreak to give security teams practical preparation guidance.
The post links to registration.
Ask for a session recording or summary to assess what was taught.
For brands planning a campaign
This shows a repeatable webinar format and the internal colleagues Desai presents with. A vendor pitching a joint session should note that past sessions were built on research partnerships, making a co-presented research angle a stronger fit than a general product pitch.
AI-driven attacks and where defenders should focus
Deepen Desai’s most sustained subject is how AI is changing both attack and defense.
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In one post, they report that Zscaler security teams tested Anthropic Mythos and OpenAI GPT 5.5 Cyber against real attack and defense scenarios and came away with three observations: multi-step reasoning lets a model build complex exploit paths rather than only scan for known vulnerabilities; architectural context improves exploit accuracy; and context should be limited to grounding the model in its own environment.
The stated conclusion is a layered defense: AI-assisted scanning across the software development lifecycle and CI/CD, Zero Trust architecture, AI-powered exposure management, and deception.
A separate post describes autonomous vulnerability discovery and machine-speed attack orchestration as the pressure security teams now face.
Publishes numbered observations from hands-on testing, names the frontier models and programs involved, and closes with a recommended combination of controls.
For brands planning a campaign
Good fit for a vendor seeking a credible voice on AI-era defense rather than generic AI hype. A co-authored piece built around a structured model-versus-model test would suit how Desai presents findings: numbered observations, a named test setup, and a defensive stack at the end.
Phishing and initial access: reading the annual data for defenders
Desai uses the Zscaler ThreatLabz 2026 Phishing and Initial Access Report to explain what changed and what to do about it.
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The findings they call out: phishing volume fell about 20% year over year while quality rose; campaigns increasingly combine email with phone, voice, or text social engineering; attackers are moving beyond credential theft toward session tokens and fast post-compromise action; and agents being phished by humans and other agents is an emerging pattern. The post boils this down to three priorities: Zero Trust with segmentation and deception to limit blast radius, phishing-resistant multi-factor authentication, and continuous security awareness training.
Extracts a handful of trend bullets from a large research report, then turns them into a short list of defensive priorities and links to the full report.
For brands planning a campaign
Desai already turns research reports into short, decision-oriented summaries, making a co-authored threat research collaboration a clear fit. A partner could sponsor or co-publish a companion analysis, with findings presented as data followed by a few concrete priorities—not a product pitch.
Agentic security operations and rebuilding the SOC
In one post, Desai centers on the launch of Zscaler’s Agentic Security Operations offering.
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They describe the problem in operational terms—fragmented tools, incomplete visibility, high data-ingestion costs, and too many manual steps—and argue that this model was already strained before AI-driven attacks and is now breaking down.
The claimed design responses are unified exposure and threat management; inline telemetry across network, identity, endpoint, cloud, AI, and deception; specialized AI agents informed by frontline SOC, managed detection and response, and threat-hunting experience; and closed-loop remediation through a Zero Trust exchange.
They also name outside participants in the launch conversation, including people from Anthropic, HDFC Bank, MAIRE, and Forrester.
Product launch storytelling that pairs the market problem with a bulleted capability list and credits customers, teams, and external speakers.
For brands planning a campaign
Desai serves as both a launch-stage spokesperson and a technical explainer. For a partner considering a joint webinar or launch-adjacent content, they frame the narrative around defender workload and response time, and credit outside practitioners by name—a useful approach if the partner wants its own customers or researchers featured.
Practitioner guidance through webinars and shared research
Desai promotes a Zscaler webinar alongside named colleagues, promising practical guidance on how security teams can prepare for AI’s impact, drawing on work with Anthropic’s Project Glasswing and OpenAI Daybreak.
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They name the shift, the programs that provided early access, and the practical preparation on offer. In the frontier-model post, they also credit Anthropic’s Project Glasswing and OpenAI’s Trusted Access for Cyber program for early access to frontier models.
For brands planning a campaign
A partnership brief that includes a webinar or panel fits Desai’s approach and the way this material is distributed. The practical ask: a preparation session grounded in named research collaborations, with a clear sign-up or registration path, rather than a broad thought-leadership keynote.
Desai's posts place them inside Zscaler's security organization: the launch announcement for Zscaler Agentic Security Operations, an invitation to a Zscaler webinar, and Zscaler ThreatLabz research are all presented in the first person as team work.
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Anthropic and OpenAI appear through frontier-model access programs that Zscaler's security team tested against and drew on for customer guidance. Ask whether any paid personal relationship exists with the named brands.
Zscaler
Employment
Desai writes about Zscaler's security work in the first person: “our teams” launching the Agentic Security Operations solution, “our security team” testing frontier AI models, a Zscaler webinar they are joining, and the Zscaler ThreatLabz 2026 Phishing and Initial Access Report.
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The posts show them speaking from inside Zscaler's security and threat research organization, with access to its platform and research output.
Anthropic's Project Glasswing gave Zscaler's security team early access to frontier models, including Anthropic Mythos, which the team tested against real attack and defense scenarios.
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Desai describes it as a trusted partnership between the defender community and the model provider. Anthropic's Brett Andrews also spoke at the Zscaler Agentic SecOps launch.
OpenAI's Trusted Access for Cyber (TAC) program provided Zscaler's security team early access to frontier models such as GPT 5.5 Cyber.
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Desai's webinar guidance draws on Zscaler's work with Project Glasswing and OpenAI Daybreak. The posts describe a technical access and testing relationship.
Deepen Desai writes about how AI is changing both attack methods and the defenses meant to stop them.
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Start with the posts breaking down the annual ThreatLabz phishing and initial access data, and the notes from testing frontier AI models against real attack and defense scenarios.
They show the approach used throughout: identify a shift, list a few findings, and close with priorities such as Zero Trust with segmentation and deception, exposure management, phishing-resistant multi-factor authentication, and continuous awareness training.
The launch post and webinar announcement bring the same arguments to security leaders deciding where to invest.
Desai sits closer to the practitioner-researcher end of the field than the executive keynote end, leaning on test observations and report figures rather than strategic slogans and pointing readers to a longer piece for detail.
Both present Zero Trust as the architectural answer to AI-driven attacks and tie their arguments to collaboration with frontier AI labs.
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Chaudhry's post on pacing AI security makes the same two-part case as Desai's: hide attack surfaces and stop lateral movement. The summit post credits named CISOs and CIOs who adopted Zero Trust, much as Desai names outside participants in a launch.
Chaudhry makes the strategic case to CEOs, CIOs, and CISOs on keynote stages, focusing on organizational inertia. Desai reports what a security team observed while testing specific models and what an annual phishing report shows, then turns those findings into a short control list.
Both start from the same premise: AI has made finding flaws cheaper and faster, shifting the constraint from discovery to remediation.
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Slavin's reading of the Verizon DBIR and the first Forrester agentic development security landscape tracks Desai's reading of the ThreatLabz phishing report. Both also respond to frontier-model programs with security implications, naming Anthropic's Project Glasswing and OpenAI's programs.
Slavin focuses on application and software supply chain security, writing as a vendor building in that space.
The work spans context graphs, an action layer with verifiable outcomes, and triage pipelines.
Desai ranges wider, covering phishing, SOC operations, exposure management, and inline telemetry across network, identity, endpoint, cloud, and deception.
Both write about how agentic AI affects security and the people responsible for it, and use their posts to direct readers to a longer conversation—an article or an interview—rather than close the argument on the platform.
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Curry's leadership post raises questions of accountability and predictability for AI-powered teams, the management side of the shift Desai describes operationally.
Curry's posts offer broader commentary and interview promotion, moving between leadership, society, and trust. Desai anchors each post in a specific data set or testing exercise and ends with a short list of defensive priorities.
A buyer can place Deepen Desai’s audience in LinkedIn security, but the available posts don’t measure who follows the account.
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The only quantified audience figure is the LinkedIn account’s follower count, dated October 2026.
Four posts from 20 May to 11 September 2026 show content aimed at security practitioners and decision-makers: a phishing and initial-access report; the launch of Zscaler’s agentic security operations offering, with named bank and analyst speakers; testing frontier AI models against real attack and defense scenarios; and a practitioner webinar with colleagues.
The posts don’t show whether followers are buyers, what share work in security, or their seniority or locations.
They also don’t publish per-post engagement, reach, or audience survey results.
For a co-hosted webinar or co-authored threat research collaboration, ask Desai or their team for platform audience demographics covering geography, age, and gender, plus employer, occupation, and job seniority data.
Request an audience survey or documented sponsor results for comparable formats, such as webinar attendance or report downloads.
Deepen Desai’s posts show Zscaler work, not personal partnership or sponsorship formats: a company webinar on AI and vulnerability management with Zscaler colleagues Dhawal Sharma, Zoltan Kovacs, and Amir Moin; a Zscaler product launch featuring speakers from Anthropic, HDFC Bank, MAIRE, and Forrester; Zscaler’s security team gaining early access to frontier models through Anthropic’s Project Glasswing and OpenAI’s Trusted Access for Cyber program; and the company’s phishing report and threat-lab blog.
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These are employer-level relationships announced by an employee.
For vendors planning a webinar or co-authored threat-research project, a pitch to Desai is effectively a pitch to Zscaler’s security organization, where public-facing thought leadership is produced under the company brand and partners are announced by the company.
Ask for confirmation of the appropriate contact, sponsorship terms, rates, and deliverables; the posts provide no sponsorship policy, rate card, media kit, contact route, or disclosed paid collaboration.
A security vendor seeking a recognized practitioner voice for a co-authored threat-research webinar is a good fit.
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Desai's posts show a strong match.
One walks readers through the Zscaler ThreatLabz 2026 Phishing and Initial Access Report and distills it into three defensive priorities: Zero Trust with segmentation and deception, phishing-resistant multi-factor authentication, and continuous security awareness training.
Another shares firsthand frontier-model testing, with three numbered observations about exploit-path reasoning, architectural context, and limiting context to grounding.
A third promotes a Zscaler webinar with named colleagues, focused on practical preparation rather than theory.
Together, these posts suit a vendor seeking a security leader who can turn research into a short, decision-oriented session and explain the test setup, findings, and defensive response.
The fit is strongest when the partner brings its own data or customer access and lets Desai provide the threat-research framing.
Because the public work is produced under the Zscaler brand, ask whether the partnership can be approved by Zscaler's security organization; the posts don't establish an independent booking route.
When to choose a specialist
A cybersecurity vendor seeking Desai as an independent, vendor-neutral paid reviewer to rank competing endpoint or SecOps platforms is a poor fit based on the public posts.
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They show Zscaler-brand thought leadership, not independent comparison work: a company report walkthrough, a Zscaler webinar with Zscaler colleagues, a Zscaler Agentic Security Operations launch, and frontier-model testing described as Zscaler security team work with named partner programs.
The launch post is product-led and credits outside speakers from Anthropic, HDFC Bank, MAIRE, and Forrester, but remains an employer product announcement.
The partnerships section documents no personal sponsorship formats, disclosed paid collaborations, media kit, or inquiry route.
A campaign requiring Desai to publish without the Zscaler frame or rank Zscaler competitors neutrally asks for something the posts don't show and may conflict with the employer role.
A non-security B2B software brand seeking broad AI-productivity thought leadership is also a poor fit.
Desai's posts focus on security operations, phishing, vulnerability discovery, and defense; they don't support general AI-adoption content.
The audience information shows a LinkedIn follower count of 9,918 recorded in October 2026, but no demographics or engagement data to assess the case for a non-security reach campaign.
A worked campaign example
A worked campaign angle for a security vendor: a 45-minute joint webinar plus a short co-authored research note titled "When the scanner starts thinking: what frontier-model testing means for defender priorities."
Desai opens with the three observations from the frontier-model testing post: multi-step reasoning lets a model build complex exploit paths rather than only scan for known vulnerabilities; architectural context improves exploit accuracy; and context should be limited to grounding the model in its own environment.
The partner presents its customer-facing angle, such as what its telemetry or incident data shows about faster post-compromise activity, tied to the phishing report finding that attackers are moving past credential theft toward session tokens.
The joint closing segment follows Desai's existing three-priority structure: Zero Trust with segmentation and deception, phishing-resistant MFA, and continuous security awareness training.
Build the research note on the same structure: a short setup describing the test conditions, three numbered observations, one worked example, and a defender checklist.
The strongest hook in Desai's posts is the report's emerging pattern of agents being phished by humans and other agents: it's specific, unfamiliar, and easy to build a joint research note around.
Before committing to promotion targets, ask Desai or the Zscaler team for platform demographics and past webinar attendance or report-download results.
Treat the collaboration as a Zscaler-approved partnership: confirm approval, speaker clearances, and any legal review before announcing names, and don't assume a personal fee, rate card, or independent booking process exists.
Choose Jay Chaudhry for a top-level executive keynote on securing enterprise AI at scale, not a narrow research walkthrough.
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Jay Chaudhry's posts show a strategy-first argument: AI security cannot be paced even if frontier-model development is debated, traditional firewall-based security is unsafe against AI agents, and Zero Trust should hide attack surfaces and stop lateral movement.
The Gartner summit post adds named customer stories from Dow and Viatris and frames the coming network as millions of autonomous AI agents.
That is a stronger choice for a CIO/CISO main-stage session that needs executive-level stakes, named enterprise examples, and a call to reduce organizational inertia.
The tradeoff is distance from hands-on threat research.
Unlike Desai’s frontier-model post, these posts argue from architecture and leadership rather than testing notes, exploit-path observations, or a practitioner checklist.
They also reflect one platform’s Zero Trust positioning, so a co-authored research note would need a partner-owned data set to avoid repeating that framing.
If the webinar must show how a test was run and what defenders observed, Desai is the better pick.
Choose Ronen Slavin for a campaign focused on application security, software supply chain, or remediation at machine speed.
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Slavin's posts treat the problem as a bottleneck shift: AI has commoditized vulnerability discovery, so the harder job is triaging, confirming exploitability, and closing risk as fast as AI finds it.
One post uses Verizon DBIR findings, including vulnerability exploitation passing stolen credentials, time-to-patch up 34%, and supply chain involvement in 48% of breaches, alongside Forrester's first Agentic Development Security Landscape to define the category.
The other covers Anthropic's Fable5 and Claude Mythos 5, Project Glasswing, OpenAI's Daybreak, and Microsoft's MDASH, all landing in the same remediation queue.
That is a sharper fit than Desai for a vendor whose product or data sits in AppSec, secure SDLC, or vulnerability remediation.
The tradeoff is scope.
Slavin’s posts center on development security and remediation rather than the broader SOC, phishing, and Zero Trust topics Desai covers.
They also build a commercial category for Cycode, so a partner campaign would need to distinguish shared technical framing from competing product claims.
If the campaign needs a phishing report walkthrough, session-token risk, or Zero Trust architecture for a general security-operations audience, Desai is the better choice.
Choose Sam Curry for leadership, workforce, and risk management in an agentic AI program rather than technical threat research.
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The posts ask how to lead non-human team members, maintain accountability when decisions are made by a network of agents, and keep predictability in non-deterministic systems.
One post points readers to an article on those leadership challenges; the other is a conversational interview with Richard Stiennon that ranges from feature usage to information use and the societal and cyber impact of agentic AI.
That is a better choice for a webinar or co-authored piece aimed at CIOs and CISOs who must reorganize teams and governance before technology outpaces management.
The tradeoff is sparse technical proof.
The posts describe questions and themes rather than a tested threat scenario, named research method, or defensive priority list.
If the campaign needs a practitioner session with numbered observations from real attack and defense testing, ask for that evidence; Desai is the stronger fit.
Four complete LinkedIn posts by Deepen Desai discuss the Zscaler ThreatLabz 2026 Phishing and Initial Access Report, frontier-model testing through Anthropic's Project Glasswing and OpenAI's Trusted Access for Cyber program, the Zscaler Agentic Security Operations launch, and an upcoming Zscaler webinar.
The posts carry no dates, and the reports, blog, event recording, and webinar registration they link to are not discussed in the posts.
The posts do not mention signature books, shows, or earlier career material, so those topics remain open research gaps.
This overview follows the overview, ideas, relationships, discovery, and fit sections and adds no claims beyond the posts.