Cox model regression - interpretation of survival graph

I fitted a Cox model and plotted that kaplan-Meier curve with a library survminer and survival in R. I got two variable "risk factor present" vs "risk factor absent". The max time recorded in cases with "risk factor present" is 1350 vs 4200 for case with "risk factor absent" (HR: 2.3 [1.4 - 5.0] p = 0.02). I got the following graph:

I think that the end of the line for "risk factor present" is a bit abrupt. I want to illustrate that the HR is higher for cases with "risk factor present". Is this graph ok so or should there be any kind of smoother stepping down of the line?

EDIT

I find this interesting article where I found a useful (to me at least) information about how to integrate the "bits of steps and straight line" integrate with the percentage on the y axis. It says: "There are two probabilities which can be confusing. There is a cumulative probability and an interval probability. The cumulative probability defines the probability at the beginning and throughout the interval. This is graphed on the Y-axis of the curve. The interval survival rate (or probability) defines the probability of surviving past the interval, i.e. still surviving after the interval and beginning the next. The first intervals characteristically begin at zero time and end just prior tot the first event. Cumulative probabilities for an interval are calculated by multiplying the interval survival rates up to that interval. The Y-axis in the curve only relates to the cumulative probability of the interval but does not tell us how many subjects were in the numerator the denominator for each interval". I guess this cumulative probability corresponds to the the "estimator" of the wiki page of kaplan meier pointed by @EdM:

$$\hat{S}(t) = \prod_{i: t_{t} \leq t }\Big(1 - \frac{d_{i}}{n_{i}} \Big)$$

where $$t_{i}$$ a time when at least one event happened, $$d_{i}$$ the number of events that happened at time $$t_{i}$$ and $$n_{i}$$ the individuals known to survive (have not yet had an event or been censored) at time $$t_{i}$$

Please let me know if this doesn't make sense