Chloe Maraina blends business intelligence with frontline security operations in retail, turning noisy telemetry into clear, visual stories leaders can act on. She’s spent peak seasons translating threat intel into hour-by-hour playbooks, compressing detection-to-containment windows when staff is thin and stores are overflowing. In this conversation with Richard Lavaile, she maps the unique risks from Thanksgiving through the New Year, showing how data, drills, and disciplined access controls can keep ransomware and social engineers from turning a critical sales window into a crisis. Themes include off-hours encryption patterns, weekend staffing realities, recon detection at the edge, identity trust in motion, and sharpening SOC runbooks for the most distracting weeks of the year.
Thanksgiving to Black Friday kicks off a critical retail window. How does your threat model change that week, and what past holiday incidents shaped it? Walk me through one example with timelines, attacker steps, and the metrics you watched hour by hour.
The week shifts our assumptions: we treat every off-hours alert as higher risk because more than half of ransomware attacks land on holidays or weekends. One Black Friday we tracked a quiet surge in failed authentications from a residential ASN right after store closings, then saw a burst of scripted portal probes as midnight approached. From there the actor tried to plant a lightweight remote tool and enumerate service accounts, aiming to return before 6 p.m.–8 a.m. when encryption tends to hit. Hour by hour we watched identity anomalies, failed MFA prompts, and east-west connections from a single compromised kiosk; we tuned containment to stop lateral movement while we reissued credentials. That experience hardened our runbooks to bias toward immediate isolation when nocturnal recon appears.
Semperis found over half of ransomware attacks hit on holidays or weekends. How do you prioritize controls for those windows, and what measurable safeguards moved the needle most? Share concrete before-and-after metrics and a specific weekend incident response play.
We stack defenses where attackers prefer to operate: identity, off-hours EDR hardening, and rapid isolation. Because more than half of attacks fall on weekends or holidays, we stage stricter conditional access beginning late afternoon and expand MFA challenges for privileged actions. On a Saturday, a payroll connector attempted unusual directory reads; our weekend play kicked in—auto-quarantine of the process, forced password resets, and a fast-track validation through our on-call lead. The practical difference was felt in how little surfaced to customer-facing systems; the safeguards turned what could be a multiday incident into a short, controlled interruption.
The report says 8 in 10 companies cut staffing by 50%+ on weekends. How do you right-size on-call rotations, escalation trees, and SLAs then? Give a step-by-step coverage plan and a story where it prevented lateral movement overnight.
We accept reduced headcount but refuse reduced clarity. Step one: preassign an incident commander for each night with clear authority. Step two: pair analysts so every alert has two sets of eyes, even remotely. Step three: publish a crisp escalation tree that jumps directly to executives for business-impacting alerts. One overnight, that plan caught a burst of credential stuffing against point-of-sale portals; the paired analysts escalated, the commander froze at-risk accounts, and we segmented the store network before the attacker could pivot inward. The tree exists to remove hesitation when minutes are most expensive.
Three in four firms have an in-house SOC. How do you adapt SOC runbooks for off-hours, and what automation handles first-touch triage? Describe your alert tuning, handoffs, and one case where automation collapsed dwell time.
Off-hours runbooks strip ambiguity. We make containment decisions binary: isolate or escalate, with no limbo states. Automation ingests identity signals, EDR detections, and change logs, then applies weekend-specific thresholds to quarantine suspicious processes and challenge risky logins. In one case, automation spotted odd scheduled-task creation on a server after closing; it isolated the host and pushed a high-urgency ticket to on-call. By the time a human joined, the host was already safe and lateral scanning attempts had nowhere to go, collapsing dwell time and preserving business continuity.
Attackers often begin entry and recon during nights and holidays. Which signals best reveal early recon in your environment, and how do you validate them fast? Walk through one detection, the artifacts you captured, and your containment steps.
We trust subtlety: odd page sequences in admin portals, directory enumeration from non-admin identities, and system discovery commands executed from endpoints that should never run them. One holiday night, we detected suspicious LDAP queries from a contractor account followed by targeted access to a configuration page. We captured process lineage, outbound DNS queries, and a snapshot of token use; that bundle told the story. We immediately disabled the session, rotated secrets tied to that account, and locked the subnet while we combed logs; it was surgical, and it stopped the recon before it matured.
Remote work and travel blur identity. How do you verify an executive or contractor logging in from a new time zone without slowing business? Share an anecdote with device trust checks, MFA prompts, and how you handled exceptions.
We front-load device trust and context. During Thanksgiving travel, an executive attempted access from a hotel network; the device was enrolled and healthy, but the location was new. Our system required an additional MFA challenge and a just-in-time elevation only after a quick confirmation in our chat channel. For exceptions, the on-call commander can grant a short-lived pass with logging, and we review those grants the next morning. The executive was in within minutes and our audit trail stayed pristine.
RH-ISAC leaders cited phishing simulations and refresher training before holidays. Which modules or scenarios reduced clicks most, and how did you measure durable behavior change? Tell a story about a near-miss that training defused.
We emphasize holiday-themed lures—shipping delays, travel itinerary changes, and urgent gift card requests. Before the season, we run expanded simulations and mandatory refreshers; we measure not just clicks but reporting speed and the quality of reports. One near-miss involved a fake vendor invoice hours before a sale; a store manager recognized the cadence mismatch from training and reported it immediately. That report triggered our blocklists and a note to all stores, cutting off the campaign before it propagated.
Marks & Spencer lost roughly $400 million after a pre-Easter social engineering attack. What early tells would you hunt for in a similar scenario, and how would you harden comms and approvals? Outline your step-by-step containment and recovery play.
Early tells include tone-shifted emails from senior leaders, sudden urgency for large transfers, and attempts to switch to unvetted channels. We lock down approvals to verified channels and require secondary sign-offs for high-impact actions. If we suspect compromise, step one is to freeze the impacted workflow, step two is to validate identities out-of-band, and step three is to rotate credentials and reissue clean devices if needed. Recovery includes targeted messaging to teams explaining what happened and why, plus a narrow reintroduction of access with heightened monitoring.
Scattered Spider drove months of retail disruptions across countries. What cross-border coordination worked, and where did it fail? Share concrete timelines, shared IOCs, and one tactic you would change if you could replay it.
What worked was early sharing of indicators and tradecraft across regions—recon patterns, initial access methods, and target lists—so we could align defenses ahead of the attackers’ time zone hops. Where we stumbled was in synchronizing containment windows; different countries had different maintenance periods, and attackers threaded the gaps. If we could replay it, we’d enforce a unified freeze and a single cross-border commander to eliminate timing seams. The lesson: shared intel is powerful, but shared decision-making is indispensable.
Google’s team saw 70% of encryptions occur between 6 p.m. and 8 a.m., and 30% on weekends. How do you stage backups, EDR policies, and kill switches before those windows? Give a detailed drill you run and the metrics that prove readiness.
We stage immutable backups and rehearse switching to them before the evening window, and we ratchet EDR to stricter policies at close of business. Our drill starts with a simulated ransomware beacon after hours, forcing the team to isolate hosts, trigger the kill switch that halts suspicious encryption behavior, and pivot to clean restores. We track whether isolation propagates quickly, whether restores begin without friction, and whether business systems remain usable. The drill is noisy by design; if it rattles no one, it probably wasn’t real enough.
Some chats suggest a late-December lull. Do you adjust coverage around that period, or treat it as deception risk? Describe the data you track, a decision you made from it, and the outcome.
We treat any lull as potential misdirection. While some activity may dip between Christmas Eve and mid-January, we still see opportunistic probes. We track off-hours alert volumes, failed authentications, and phishing attempts; our decision was to keep holiday coverage firm rather than relax. The outcome was a quiet season for us—quiet because we stayed ready, not because adversaries were resting.
CISA flagged increased seasonal risk without specific threats. How do you use CISA advisories and ISAC intel in real time? Walk through one intel-to-action pipeline, including tooling, validation, and the measurable impact.
We funnel advisories into our intel platform, auto-tagging them by relevance to identity, endpoint, or third-party risk. From there, we generate detections and lightweight hunts, then validate by testing against our logs and running a safe simulation. If signals fire, we turn temporary controls into hardened policy and push short briefs to operations and leadership. The impact shows up in cleaner alert queues and fewer surprises during off-hours.
Identity and access tighten during holidays. Which access reviews, privilege clamps, and just-in-time workflows do you enforce, and how do you handle break-glass? Share one incident where least privilege contained spread.
We run targeted access reviews before the peak and clamp privileges for dormant roles, shifting high-risk tasks to just-in-time access with auto-expiry. Break-glass is tightly scoped, logged, and reviewed the next morning. In one incident, a compromised partner account tried to enumerate internal dashboards; least privilege walled it off to a narrow slice of noncritical data, buying us time to revoke access. That boundary was the difference between a nuisance and a narrative.
Tabletops get “more frequent and realistic” before peak season. What scenario produced the best learning, and how did you score teams? Detail injects, decision points, and the exact improvements shipped afterward.
Our best exercise mimicked an off-hours ransomware attempt targeting store servers and identity sync. Injects included misleading alerts, vendor noise, and a simulated executive asking for a risky exception. Decision points forced trade-offs between immediate isolation and maintaining sales systems. We scored clarity of command, speed of isolation, and communication quality; afterward we shipped tighter isolation scripts, a crisper exception policy, and more resilient backup job scheduling.
Personal devices and family-shared networks complicate controls. What minimum standards, MAM/MDM controls, and network checks do you require, and how do you verify compliance fast? Give an example where those gates blocked a real threat.
Minimum standards include up-to-date OS, disk encryption, and healthy endpoint agents. We enforce app-level controls for corporate data, verify device posture at login, and check basic network hygiene even on home or hotel Wi-Fi. One holiday, a personal laptop failed posture due to a disabled protection service; access was blocked and the user moved to a managed device. That small friction spared us a bigger headache.
Vendors and contractors surge during promotions. How do you vet third-party access, monitor service accounts, and freeze risky changes? Tell a story where third-party telemetry helped you stop a late-night intrusion.
We tighten third-party scopes, require their logs feed into ours, and put change freezes around promotions. One late night, partner telemetry showed unusual directory probing from a shared account; our monitors matched it to internal anomalies, so we froze the account and paused the integration. The partner patched a misconfiguration while we rotated keys. Without their signals, we might have chased ghosts until morning.
Metrics matter during off-hours. Which KPIs—MTTD, MTTR, containment time, and blast radius—do you monitor live, and what thresholds trigger leadership calls? Share a dashboard snapshot and one intervention it drove.
We keep MTTD, MTTR, containment time, and blast radius front and center, plus the age of the oldest untriaged alert. If blast radius widens beyond a single segment or containment stalls, we call leadership immediately. One dashboard spike in identity anomalies prompted us to tighten access policies and add extra verification for privileged actions that night. The ripple effects were immediate: fewer escalations and steadier operations.
After the first January workweek, what postmortem ritual do you run? Explain the data you gather, the root-cause method you use, and one control you added that measurably reduced weekend exposure.
We close the season with a deep dive: alert flows, ticket histories, escalation timestamps, and training outcomes. We use a structured question set to get to root causes, probing not just what broke but why the system allowed it. A key control we added was stricter off-hours identity challenges for privileged tasks, directly aligned to the pattern that most encryptions occur outside working hours. Weekend exposure dropped in a way our teams could feel—less noise, more signal, and faster decisions.
Do you have any advice for our readers?
Treat the holidays like a known weather pattern, not a surprise storm. Lean into the data that shows when attackers operate—on holidays, on weekends, and between 6 p.m. and 8 a.m.—and pre-stage your defenses accordingly. Simplify decisions for sleepy humans, give automation the first swing, and keep identity trust front and center. Most of all, rehearse under realistic pressure so your team’s first hard call of the season isn’t during a real crisis.
