Looking for the most recent Mini Crossword answer? Click here for today’s Mini Crossword hints, as well as our daily answers and hints for The New York Times Wordle, Strands, Connections and Connections: Sports Edition puzzles.

Need some help with today’s Mini Crossword? It’s the longest of the week, the Saturday edition. Read on for all the answers. And if you could use some hints and guidance for daily solving, check out our Mini Crossword tips.

If you’re looking for today’s Wordle, Connections, Connections: Sports Edition and Strands answers, you can visit CNET’s NYT puzzle hints page.

Read more: Tips and Tricks for Solving The New York Times Mini Crossword

Let’s get to those Mini Crossword clues and answers.

Mini across clues and answers

1A clue: N.B.A. team that plays at M.S.G.
Answer: KNICKS

7A clue: Guy with a nerdy, passionate interest
Answer: FANBOY

8A clue: Rudely merges
Answer: CUTSIN

9A clue: Standard number of bowling pins
Answer: TEN

10A clue: Inflated sense of one’s own importance
Answer: BIGEGO

13A clue: Arrived via airplane
Answer: FLEWIN

14A clue: History-making achievements, perhaps
Answer: FIRSTS

Mini down clues and answers

1D clue: Colonel Sanders’s fast-food chain
Answer: KFC

2D clue: Spiral-shelled mollusks
Answer: NAUTILI

3D clue: 1, 2 or 3, but not 1.23
Answer: INTEGER

4D clue: “60 Minutes” producer
Answer: CBSNEWS

5D clue: Colorful pond fish
Answer: KOI

6D clue: Thesaurus listing: Abbr.
Answer: SYN

10D clue: Closest pal, for short
Answer: BFF

11D clue: “Go on, ___!” (“Scram!”)
Answer: GIT

12D clue: Opposite of offs
Answer: ONS

Good morning! Let’s play Connections, the NYT’s clever word game that challenges you to group answers in various categories. It can be tough, so read on if you need Connections hints.

What should you do once you’ve finished? Why, play some more word games of course. I’ve also got daily Strands hints and answers and Quordle hints and answers articles if you need help for those too, while Marc’s Wordle today page covers the original viral word game.

After 10 days, the four astronauts aboard the Orion spacecraft have returned to Earth, their mission around the Moon a success.

Integrity, the name of the crew’s spacecraft as part of NASA’s Artemis II mission, splashed down in the Pacific Ocean off the coast of San Diego, California, at 5:07 p.m. Pacific Time, according to NASA. The four crew members aboard — three Americans and one Canadian — were all in “green” (or safe and healthy) condition after the Orion craft’s “perfect” landing.

The crew was composed of Commander Reid Wiseman, pilot Victor Glover, and mission specialists Christina Koch and Jeremy Hansen. From liftoff to splashdown, the quartet was in space for just over nine days (with NASA rounding up and calling it a 10-day mission).

Artemis II was NASA’s first mission to the Moon’s orbit in more than 50 years. The crew traveled farther from Earth than humans ever have before — reaching an estimated 252,760 miles from our planet. During their journey, the crew orbited the Moon, taking photos from their flyby of never-before-seen parts of the surface, and even witnessing a total solar eclipse. They identified new craters, naming one after Wiseman’s wife Carroll, who died of cancer in 2020.

“These were the ambassadors to the stars that we sent out there,” Jared Isaacman, NASA’s administrator, said after the landing. “I can’t imagine a better crew. It was a perfect mission.”

Isaacman, a commercial astronaut who has been on two private orbital missions, also took to X to celebrate the mission and signaled there would be more to come, noting that America is back in the business.

“America is back in the business of sending astronauts to the Moon and bringing them home safely,” he wrote on X, later giving credit to the entire NASA workforce. “This was a test mission, the first crewed flight of SLS and Orion, pushing farther into the unforgiving environment of space than ever before, and it carried real risk. They accepted that risk for all we stood to learn and for the exciting missions that follow, as we return to the lunar surface, build a Moon base, and prepare for what comes next.”

This weekend’s watchlist covers three different genres of movies, so you can pick whatever you are in the mood for. We have a trio of hidden gems on Amazon Prime Video that deserve way more attention.

There is a gritty Michael Caine revenge thriller you should not miss, a micro-budget 1950s sci-fi mystery that thrives on atmosphere and dialogue. For horror fans, we have a psychological horror bout a hospice nurse whose faith tips into something far more dangerous that gets inside your skin.

We also have guides to the best new movies to stream, the best movies on Netflix, the best movies on Hulu, the best free movies, and the best movies on Amazon Prime Video.

Saint Maud (2019)

Saint Maud is not a horror film in the traditional sense, and going in expecting one will work against you. What it actually is is a deeply unsettling psychological portrait of a young hospice nurse named Maud, a recent Catholic convert who becomes dangerously fixated on saving her terminally ill patient’s soul in ways that grow increasingly disturbing.

Morfydd Clark’s performance is the engine of the whole thing, holding a fragile, frightening line between piety and paranoia throughout. I really like how the film gets under your skin without ever fully explaining itself. You finish it feeling like you witnessed something you were not supposed to see, and that feeling does not leave quickly.

You can watch Saint Maud on Amazon Prime Video

Harry Brown (2009)

If you have a soft spot for slow-burn British crime dramas, Harry Brown is the movie you need to watch this weekend. Michael Caine plays the title character, a widowed, retired Royal Marines veteran living on a decaying South London housing estate overrun by gang violence. When his only friend is murdered, Harry stops looking the other way.

What makes this film work so well is how it refuses to glamorize what follows. Harry is not an action hero. He is an old man with emphysema who stumbles during a chase and collapses on a canal path.

I really like how the film earns every moment of tension because it keeps Harry vulnerable and the world around him genuinely threatening. Caine is absolutely extraordinary here, and there are sequences in this film that will make you forget you are watching a 77-year-old man.

You can watch Harry Brown on Amazon Prime Video

The Vast of Night (2019)

Have you accidentally tuned into a late-night radio broadcast and could not bring yourself to switch off. Well, The Vast of Night is exactly that kind of sci-fi movie.

Set over a single night in 1950s small-town New Mexico, the film follows Fay, a teenage switchboard operator, and Everett, a fast-talking local radio DJ, as they stumble onto a mysterious audio frequency that sends them down a strange and increasingly eerie rabbit hole.

There are no big set pieces or alien invasions. The tension is built almost entirely through dialogue, long unbroken camera takes, and an incredibly precise sound design that makes the night feel alive and watchable.

What I really love about this movie is how it makes stillness feel tense. A long phone call, a quiet street, a voice crackling through static, and somehow all of it keeps you completely locked in. For a movie made on a low budget, The Vast of Night makes an entertaining watch.

You can watch The Vast of Night on Amazon Prime Video

HappyHorse 1.0 shot up to the top ranks in the Artificial Analysis leaderboard.

Chinese technology giant Alibaba’s cloud division led a $293m funding round into ShengShu Technology, a 2023-founded Beijing-based start-up behind the Vidu AI video-generation tool.

Baidu Ventures and Luminous Ventures also participated in the round. The company’s post-money valuation has not been disclosed.

The latest investment comes after ShengShu raised nearly $88m in a Series A round in February.

Vidu is marketed towards independent creators and animators, promising “effortless” production of content with “diverse artistic styles”.

The start-up is focusing on building ‘world models’ built on multimodal data such as audio, video and “touch”. The latest funding, the company said, will help support the development of a “general world model”.

The company’s latest Vidu Q3 Pro, which launched in January, places at the seventh rank on the Artificial Analysis leaderboard on text-to-video models, while making it to the 10th spot on the image-to-video rankings.

Vidu competes with other Chinese AI heavyweights, including ByteDance’s Seedance 2.0 and lead investor Alibaba’s own video model HappyHorse 1.0 that shot up to the top rank on the Artificial Analysis leaderboard.

Meanwhile, models from companies such as Singapore’s Skywork AI and Beijing-based Kuaishou, behind KlingAI, also rank high on the boards. These models are hungry to fill the gap in the video generation space left by OpenAI after it shuttered Sora late last month. Top leaderboard rankings are increasingly being filled by Chinese models.

HappyHorse was anonymously launched earlier this week before Alibaba claimed ownership today (10 April). The model is a product of Alibaba’s new Token Hub (ATH) innovation unit, placing number one on text-to-video and image-to-video ranks with no audio, while placing at the second spot with audio.

Bloomberg News reported that HappyHorse 1.0, which is under beta testing currently, will be followed up with more new ATH products. Alibaba’s share prices shot up following speculation that the company was behind the model.

Alibaba made the decision last month to bring its AI services and development works under a single roof called ATH, led by CEO Eddie Wu.

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Author: Saeed Abbasi, Senior Manager, Threat Research Unit, Qualys

With Time-to-Exploit now at negative seven days and autonomous AI agents accelerating threats, the data no longer supports incremental improvement. The architecture of defense must change.

What Leaders Need to Know

Analysis of CISA’s Known Exploited Vulnerabilities over the past four years shows critical vulnerabilities still open at Day 7 worsened from 56% to 63% despite teams closing 6.5x more tickets. Staffing cannot solve this.

Of the 52 tracked weaponized vulnerabilities in our study, 88% were patched more slowly than they were exploited — half were weaponized before any patch existed.

The problem is not speed. It is the operational model itself.

Cumulative exposure, not CVE counts, is the true risk metric that security teams now need to measure. While dashboards reward the sprint to get patches implemented, breaches exploit the tail. AI is not another attack surface — instead, the transition period where AI-powered attackers face human defenders is the industry’s most dangerous window.

In response, defenders have to implement their own autonomous, closed-loop risk operations.

The Broken Physics

New research from the Qualys Threat Research Unit, analyzing more than one billion CISA KEV remediation records from across 10,000 organizations over four years, quantifies what the industry has long suspected but never proved at scale. The operational model underpinning enterprise security is broken.

Vulnerability volumes have grown 6.5 times since 2022. According to Google M-Trends 2026, the average Time-to-Exploit has collapsed to negative seven days; in other words, adversaries are weaponizing the most serious vulnerabilities before patches exist. The percentage of critical vulnerabilities still open at seven days has climbed from 56 percent to 63 percent.

Yet this is not for lack of effort. Organizations closed 400 million more vulnerability events annually now than they did at baseline. Teams work harder, but it fails to make the difference where it counts. Our researchers call this the “human ceiling” — a structural limit no amount of staffing or process maturity can overcome. The constraint is not effort. It is the model itself.

Of 52 high-profile weaponized vulnerabilities tracked with complete exploitation timelines, 88 percent were remediated slower than they were exploited. As an example, Spring4Shell was exploited two days before disclosure, yet the average enterprise needed 266 days to remediate.

Similarly, the flaw in Cisco IOS XE was weaponized a month early; average close was 263 days.

The attacker’s advantage was measured in days. The defender’s response was measured in seasons. This is not an intelligence failure. It is an operationalization failure.

The Manual Tax and Risk Mass

The report identifies a “Manual Tax” — the multiplier effect where long-tail assets that human processes cannot reach drag exposure from weeks into months. For Spring4Shell, average remediation was 5.4 times the median.

The median tells a manageable story. The average tells the truth. Infrastructure systems face a harsher reality: for Cisco IOS XE, even the median was 232 days — compared to endpoint medians consistently under 14. When the best-case outcome is eight months, the Manual Tax is no longer a multiplier. It is the baseline.

Looking at average figures is no longer helpful for decision-making. Instead, looking at Risk Mass — vulnerable assets multiplied by days exposed — captures what CVE counts obscure around cumulative exposure. A companion metric, Average Window of Exposure (AWE), measures the full duration from weaponization to remediation across the environment.

As an example, Follina was weaponized 30 days before disclosure with an average close at Day 55.

However, the AWE stretched to 85 days. While the blind spot before disclosure accounted for 36 percent of that 85 days, the long tail of patching accounted for a further 44 percent. In total, pre-disclosure and long tail together represent 80 percent. The sprint that gets measured makes up less than 20.

At the same time, of 48,172 vulnerabilities disclosed in 2025, only 357 were remotely exploitable and actively weaponized. Organizations are burning remediation cycles on theoretical exposure while genuinely exploitable gaps persist.

Why the Gap Will Widen

Cybersecurity has long operated as a derivative of technology shifts — Windows security followed Windows, cloud security followed cloud. Leading practitioners and investors now argue AI breaks that pattern. It is not merely a new surface to defend; it is a fundamental transformation of the adversary itself.

Offensive agents can already discover, weaponize, and execute faster than any human-staffed operation can respond. The remediation data proves humans cannot keep pace today. Autonomous AI ensures the gap will accelerate tomorrow.

The transition period — where AI-powered attackers face human-speed defenders — represents the industry’s most dangerous window, compounded by the structural vulnerabilities that dominate the near term: attack surfaces expanded beyond what teams can govern, identity sprawl that outpaces policy, and remediation workflows still built on manual execution.

The traditional scan-and-report model was built for lower volumes of CVEs and longer exploit timelines. What replaces it is an end-to-end Risk Operations Center: embedded intelligence arriving as machine-readable decision logic, active confirmation validating whether a vulnerability is actually exploitable in a specific environment, and autonomous action compressing response to the timescale the threat demands.

The objective is not to eliminate human judgment but to elevate it, shifting practitioners from tactical execution to governing the policies that direct their own autonomous systems.

The organizations already winning the physics gap are not winning with larger teams. They are winning because they have removed human latency from the critical path.

How Security Teams can close the Risk Gap

The scan-and-report model — discover, score, ticket, manually route — was built for lower volumes and longer exploit timelines.

What replaces it is an end-to-end Risk Operations Center: embedded intelligence arriving as machine-readable decision logic, active confirmation validating whether a vulnerability is actually exploitable in a specific environment, and autonomous action compressing response to the timescale the threat demands.

The objective is not to eliminate human judgment but to elevate it — shifting practitioners from tactical execution to governing the policies that direct autonomous systems. The organizations already winning the physics gap are not winning with larger teams. They are winning because they have removed human latency from the critical path.

Time-to-Exploit will not return to positive numbers. Vulnerability volume will not plateau. The reactive model has hit a hard mathematical ceiling.

The only remaining question is whether organizations will use the architecture to match the mathematics — before the window between human-scale defense and autonomous-scale offense closes for good.

Sponsored and written by Qualys.